Fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients

This research aimed to improve the fault tolerance of healthcare services provided forChronic Heart Disease (CHD) patients living in remote areas. A new fault-tolerantmHealth framework was proposed to solve existing problems in healthcare services dueto frequent failures in the telemedicine architec...

Full description

Saved in:

Bibliographic Details
Main Author:	Albahri, Ahmed Shihab Ahmed
Format:	thesis
Language:	eng
Published:	2019
Subjects:	R Medicine
Online Access:	https://ir.upsi.edu.my/detailsg.php?det=6353
Tags:	Add Tag No Tags, Be the first to tag this record!

id	oai:ir.upsi.edu.my:6353
record_format	uketd_dc
institution	Universiti Pendidikan Sultan Idris
collection	UPSI Digital Repository
language	eng
topic	R Medicine
spellingShingle	R Medicine Albahri, Ahmed Shihab Ahmed Fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients
description	This research aimed to improve the fault tolerance of healthcare services provided forChronic Heart Disease (CHD) patients living in remote areas. A new fault-tolerantmHealth framework was proposed to solve existing problems in healthcare services dueto frequent failures in the telemedicine architecture. This study used an experimentalresearch design that was carried out based on two stages. In the first stage, the researcherproposed a new algorithm known as Three-level Localization Triage (3LLT) to excludethe triage process from a medical center (Tier 3) and to overcome alarm failures relatedto Tier 1. In the second stage, the proposed framework was used to assist the decisionmaker to make the appropriate hospital selection based on a Multi-Criteria DecisionMaking technique, namely the Analytic Hierarchy Process (AHP). Two datasets wereused comprising a dataset of 572 CHD patients and a dataset of hospitals healthcareservices, which were used in the triage stage and in the hospital selection stage,respectively, based on two scenarios. The first scenario involved real high-level servicesof 12 hospitals located in Baghdad, Iraq, and the second scenario was based on low-levelsimulated services of 12 hospitals located in Kuala Lumpur, Malaysia. The resultsshowed that the AHP technique was highly effective in solving the failures of healthcareservices and the problems related to hospital selection. Moreover, the results showedsignificant differences in the groups scores, indicating that the ranking results wereidentical for the three groups. Clearly, such empirical results suggest that the ranking ofhospitals cannot be determined in a specific situation with many combined factors thatmay have a significant impact on the priority setting at the hospital level. For thevalidation of the framework, the results showed that the ranking results were perfectlyidentical. The implication of this study is that medical organizations can use the proposedfault-tolerant framework to assign patients to appropriate hospitals that can provide themwith prompt, effective healthcare services.
format	thesis
qualification_name
qualification_level	Doctorate
author	Albahri, Ahmed Shihab Ahmed
author_facet	Albahri, Ahmed Shihab Ahmed
author_sort	Albahri, Ahmed Shihab Ahmed
title	Fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients
title_short	Fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients
title_full	Fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients
title_fullStr	Fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients
title_full_unstemmed	Fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients
title_sort	fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients
granting_institution	Universiti Pendidikan Sultan Idris
granting_department	Fakulti Seni, Komputeran dan Industri Kreatif
publishDate	2019
url	https://ir.upsi.edu.my/detailsg.php?det=6353
_version_	1747833258332127232
spelling	oai:ir.upsi.edu.my:63532021-10-25 Fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients 2019 Albahri, Ahmed Shihab Ahmed R Medicine This research aimed to improve the fault tolerance of healthcare services provided forChronic Heart Disease (CHD) patients living in remote areas. A new fault-tolerantmHealth framework was proposed to solve existing problems in healthcare services dueto frequent failures in the telemedicine architecture. This study used an experimentalresearch design that was carried out based on two stages. In the first stage, the researcherproposed a new algorithm known as Three-level Localization Triage (3LLT) to excludethe triage process from a medical center (Tier 3) and to overcome alarm failures relatedto Tier 1. In the second stage, the proposed framework was used to assist the decisionmaker to make the appropriate hospital selection based on a Multi-Criteria DecisionMaking technique, namely the Analytic Hierarchy Process (AHP). Two datasets wereused comprising a dataset of 572 CHD patients and a dataset of hospitals healthcareservices, which were used in the triage stage and in the hospital selection stage,respectively, based on two scenarios. The first scenario involved real high-level servicesof 12 hospitals located in Baghdad, Iraq, and the second scenario was based on low-levelsimulated services of 12 hospitals located in Kuala Lumpur, Malaysia. The resultsshowed that the AHP technique was highly effective in solving the failures of healthcareservices and the problems related to hospital selection. Moreover, the results showedsignificant differences in the groups scores, indicating that the ranking results wereidentical for the three groups. Clearly, such empirical results suggest that the ranking ofhospitals cannot be determined in a specific situation with many combined factors thatmay have a significant impact on the priority setting at the hospital level. For thevalidation of the framework, the results showed that the ranking results were perfectlyidentical. The implication of this study is that medical organizations can use the proposedfault-tolerant framework to assign patients to appropriate hospitals that can provide themwith prompt, effective healthcare services. 2019 thesis https://ir.upsi.edu.my/detailsg.php?det=6353 https://ir.upsi.edu.my/detailsg.php?det=6353 text eng closedAccess Doctoral Universiti Pendidikan Sultan Idris Fakulti Seni, Komputeran dan Industri Kreatif A.A Zaidan, B.B Zaidan, Al-Haiqi. A, Kiah M.L.M, Hussain.M, A. . (2014). Evaluationand selection of opensource EMR software packages. Elsevier, 53, N/A.Acampora, G., Cook, D. J., Rashidi, P., & Vasilakos, A. V. (2013). A survey on ambient intelligence in healthcare. Proceedings of the IEEE, 101(12), 24702494.https://doi.org/10.1109/JPROC.2013.2262913Adibi, S. (2015). A mobile health network disaster management system. In 2015 Seventh InternationalConference on Ubiquitous and Future Networks (pp. 424428). IEEE.https://doi.org/10.1109/ICUFN.2015.7182579Adunlin, G., Diaby, V., & Xiao, H. (2015). Application of multicriteria decision analysis in healthcare: a systematic review and bibliometric analysis. Health Expectations : An International Journalof Public Participation in Health Care and Health Policy, 18(6), 1894905.https://doi.org/10.1111/hex.12287Ahmadi-Javid, A., Seyedi, P., & Syam, S. S. (2017). A survey of healthcare facilitylocation. Computers and Operations Research, 79, 223263.https://doi.org/10.1016/j.cor.2016.05.018Ahmadi, H., Nilashi, M., & Ibrahim, O. (2014). Organizational decision to adopt hospitalinformation system: An empirical investigation in the case of Malaysian public hospitals. International Journal of Medical Informatics, 84(3), 166188.https://doi.org/10.1016/j.ijmedinf.2014.12.004Ahmed, A., Rebeiro-Hargrave, A., Nohara, Y., Kai, E., Hossein Ripon, Z., & Nakashima,N. (2014). Targeting morbidity in unreached communities using portable health clinicsystem. In IEICE Transactions on Communications (Vol. E97B, pp. 540 545).https://doi.org/10.1587/transcom.E97.B.540Ahn, J., Heo, J., Lim, S., & Kim, W. (2008). A study on Ubiquitous Healthcare system based on LBS.In World Congress on Engineering 2008, Vols I-Ii (Vol. I, pp. 270 273). IEEE.Akdag, H., Kalayci, T., Karagoz, S., Zulfikar, H., Giz, D. (2014). The evaluation ofhospital service quality by fuzzy MCDM, Applied Soft Computing. Applied Soft Computing,23, 239248.Akdag, H., Kalayc?, T., Karagz, S., Zlfikar, H., Giz, D., & Akdag, H., Kalayci, T.,Karagoz, S., Zulfikar, H., Giz, D. (2014). The evaluation of hospital service quality by fuzzyMCDM, Applied Soft Computing. Applied Soft Computing, 23, 239248.Albahri, O. S., Zaidan, A. A., Zaidan, B. B., Hashim, M., Albahri, A. S., & Alsalem, M.A. (2018). Real-Time Remote Health-Monitoring Systems in a Medical Centre: A Review of theProvision of Healthcare Services-Based Body Sensor Information, Open Challenges andMethodological Aspects. Journal of Medical Systems, 42(9), 164.https://doi.org/10.1007/s10916-018-1006-6Aldlaigan, A. H., & Buttle, F. A. (2002). SYSTRA?SQ: a new measure of bank service quality.International Journal of Service Industry Management, 13(4), 362381.https://doi.org/10.1108/09564230210445041Ali, R., Siddiqi, M. H., Idris, M., Ali, T., Hussain, S., Huh, E. N., Lee, S.(2015).GUDM: Automatic generation of unified datasets for learning and reasoning inhealthcare. Sensors (Switzerland), 15(7), 1577215798. https://doi.org/10.3390/s150715772Almadani, B., Saeed, B., & Alroubaiy, A. (2016). Healthcare systems integration using Real Time Publish Subscribe (RTPS) middleware. Computers and Electrical Engineering, 50(May),6778. https://doi.org/10.1016/j.compeleceng.2015.12.009Alnanih, R., Ormandjieva, O., & Radhakrishnan, T. (2013). Context-based and rule- basedadaptation of mobile user interfaces in mHealth. Procedia Computer Science, 21, 390397.https://doi.org/10.1016/j.procs.2013.09.051Ar, I. M., & Kurtaran, A. (2013). Evaluating the Relative Efficiency of CommercialBanks in Turkey: An Integrated AHP/DEA Approach. International Business Research, 6(4),129. https://doi.org/10.5539/ibr.v6n4p129Armbrust, M., Stoica, I., Zaharia, M., Fox, A., Griffith, R., Joseph, A. D., Rabkin, A. (2010).A view of cloud computing. Communications of the ACM, 53(4), 50.https://doi.org/10.1145/1721654.1721672Aruldoss, M. (2013). A Survey on Multi Criteria Decision Making Methods and ItsApplications. American Journal of Information Systems, 1(1), 3143.https://doi.org/10.12691/ajis-1-1-5Ashour, O. M., & Okudan, G. E. (2010). Fuzzy AHP and utility theory based patientsorting in emergency departments. International Journal of CollaborativeEnterprise, 1(3/4), 332. https://doi.org/10.1504/IJCENT.2010.038357Auerbach, P. S. (1991). Health and medical aspects of disaster preparedness. Jama (Vol. 265). Springer Science & Business Media.https://doi.org/10.1001/jama.1991.03460180121047Auffray, C., Balling, R., Barroso, I., Bencze, L., Benson, M., Bergeron, J., Zanetti, G. (2016).Making sense of big data in health research: Towards an EU action plan. GenomeMedicine, 8(1), 113. https://doi.org/10.1186/s13073-016-0323-yAustralia, M. T. A. o. (2012). (n.d.). A telehealth strategy for Australia: supportingpatients in the community. Retrieved from San Diego, USA: Australia, M. T. A. o. (2012). ATelehealth Strategy for Australia: Supporting Patients in the Community. Retrieved fromHttp://Mtaa.Org.Au/Docs/Position-Papers/Supporting-a-Telehealth-Strategyfor-Australia-Release-Version-M.Azeez, D., Ali, M. A. M., Gan, K. B., & Saiboon, I. (2013). Comparison of adaptiveneuro-fuzzy inference system and artificial neutral networks model to categorize patients in the emergency department. SpringerPlus, 2(1), 110.https://doi.org/10.1186/2193-1801-2-416Azeredo, T. R. M., Guedes, H. M., Rebelo de Almeida, R. A., Chianca, T. C. M., &Martins, J. C. A. (2015). Efficacy of the manchester triage system: A systematicreview. International Emergency Nursing, 23(2), 4752.https://doi.org/10.1016/j.ienj.2014.06.001Baehr, D., McKinney, S., Quirk, A., & Harfoush, K. (2014). On the practicality of elliptic curvecryptography for medical sensor networks. In 2014 11th Annual High Capacity OpticalNetworks and Emerging/Enabling Technologies (Photonics for Energy), HONET-PfE 2014 (pp. 4145). IEEE.https://doi.org/10.1109/HONET.2014.7029358Baig, M. M., & Gholamhosseini, H. (2013). Smart health monitoring systems: Anoverview of design and modeling. Journal of Medical Systems, 37(2).https://doi.org/10.1007/s10916-012-9898-zBaltussen, R., & Niessen, L. (2006). Priority setting of health interventions: The need formulti-criteria decision analysis. Cost Effectiveness and Resource Allocation, 4(1), 14.https://doi.org/10.1186/1478-7547-4-14Barbera, Joseph A., A. G. M. (2004). Medical Surge Capacity and Capability : AManagement System for Integrating Medical and Health Resources During Large- Scale Emergencies. Department of Health and Human Services.The CNA Corporation. Washington, DC: USDepartment of Health and Human Services.Barrios, M. A. O., De Felice, F., Negrete, K. P., Romero, B. A., Arenas, A. Y., & Petrillo,A. (2016). An AHP-Topsis Integrated Model for Selecting the Most Appropriate Tomography Equipment. International Journal of Information Technology & Decision Making, 15(04),861885. https://doi.org/10.1142/S021962201640006XBarsan, W. G., Brott, T. G., Broderick, J. P., Haley, E. C., Levy, D. E., & Marler, J. R. (1993).Time of Hospital Presentation in Patients With Acute Stroke. Archives of Internal Medicine, 153(22), 25582561.https://doi.org/10.1001/archinte.1993.00410220058006Bashshur, R. L., Shannon, G. W., Smith, B. R., Alverson, D. C., Antoniotti, N., Barsan,W. G., Yellowlees, P. (2014). The Empirical Foundations of Telemedicine Interventionsfor Chronic Disease Management. Telemedicine and E-Health, 20(9), 769800.https://doi.org/10.1089/tmj.2014.9981Beck, C., & Georgiou, J. (2016). A wearable, multimodal, vitals acquisition unit forintelligent field triage. Proceedings - IEEE International Symposium on Circuits and Systems,2016July(3), 15301533. https://doi.org/10.1109/ISCAS.2016.7538853Beikkhakhian, Y., Javanmardi, M., Karbasian, M., & Khayambashi, B. (2015). Theapplication of ISM model in evaluating agile suppliers selection criteria and ranking suppliersusing fuzzy TOPSIS-AHP methods. Expert Systems with Applications, 42(1516), 62246236.https://doi.org/10.1016/j.eswa.2015.02.035Bellod Cisneros, J. L., & Lund, O. (2017). KmerFinderJS: A Client-Server Method For Fast SpeciesTyping Of Bacteria Over Slow Internet Connections. Doi.Org, 145284. https://doi.org/10.1101/145284Ben Elhadj, H., Elias, J., Chaari, L., & Kamoun, L. (2016). Multi-Attribute DecisionMaking Handover Algorithm for Wireless Body Area Networks. Computer Communications,81, 97108. https://doi.org/10.1016/j.comcom.2016.01.007Ben Othman, S., Zgaya, H., Hammadi, S., Quilliot, A., Martinot, A., & Renard, J. M.(2016). Agents endowed with uncertainty management behaviors to solve amultiskill healthcare task scheduling. Journal of Biomedical Informatics, 64, 2543.https://doi.org/10.1016/j.jbi.2016.08.011Benmansour, T., Ahmed, T., & Moussaoui, S. (2016). Performance Evaluation of IEEE802.15.6 MAC in Monitoring of a Cardiac Patient. In 2016 IEEE 41st Conference on Local ComputerNetworks Workshops (LCN Workshops) (pp. 241247). IEEE. https://doi.org/10.1109/LCN.2016.054Beratarrechea, A., Lee, A. G., Willner, J. M., Jahangir, E., Ciapponi, A., & Rubinstein,A. (2014). The Impact of Mobile Health Interventions on Chronic DiseaseOutcomes in Developing Countries: A Systematic Review. Telemedicine and E-Health, 20(1), 7582. https://doi.org/10.1089/tmj.2012.0328Berglas, N. F., Battistelli, M. F., Nicholson, W. K., Sobota, M., Urman, R. D., & Roberts,S. C. M. (2018). The effect of facility characteristics on patient safety, patientexperience, and service availability for procedures in non-hospital-affiliatedoutpatient settings: A systematic review. PloS One, 13(1), e0190975.Bernocchi, P., Scalvini, S., Tridico, C., Borghi, G., Zanaboni, P., Masella, C., Marzegalli, M. (2012). Healthcare continuity from hospital to territory in Lombardy: TELEMACOproject. American Journal of Managed Care, 18(3), 101108.Besaleva, L. I., & Weaver, A. C. (2013). Mobile Electronic Triaging for EmergencyResponse Information. 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 10921093.https://doi.org/10.1197/aemj.9.3.255.Besaleva, L. I., & Weaver, A. C. (2014). CrowdHelp: M-Health application foremergency response improvement through crowdsourced and sensor-detected information.In 2014 Wireless Telecommunications Symposium (pp. 15). New York, New York, USA: IEEE.https://doi.org/10.1109/WTS.2014.6835005Bharatula, S., & Meenakshi, M. (2016). Design of Cognitive Radio Network for Hospital Management System. Wireless Personal Communications, 90(2), 10211038.https://doi.org/10.1007/s11277-016-3280-2Bicen, A. O., & Akan, O. B. (2011). Reliability and congestion control in cognitive radio sensor networks. Ad Hoc Networks, 9(7), 11541164.https://doi.org/10.1016/j.adhoc.2011.01.004Boatin, A. A., Wylie, B. J., Goldfarb, I., Azevedo, R., Pittel, E., Ng, C., & Haberer, J. E.(2016). Wireless Vital Sign Monitoring in Pregnant Women: A Functionality andAcceptability Study. Telemedicine and E-Health, 22(7), 564571.https://doi.org/10.1089/tmj.2015.0173Bouakaz, S., Vacher, M., Bobillier Chaumon, M. E., Aman, F., Bekkadja, S., Portet, F., Chevalier, T. (2014). CIRDO: Smart companion for helping elderly to live at home forlonger. Irbm, 35(2), 100108. https://doi.org/10.1016/j.irbm.2014.02.011Boursalie, O., Samavi, R., & Doyle, T. E. (2015). M4CVD: Mobile machine learning modelfor monitoring cardiovascular disease. In Procedia Computer Science (Vol. 63, pp. 384391).Elsevier Ireland Ltd. https://doi.org/10.1016/j.procs.2015.08.357Bradai, N., Chaari Fourati, L., & Kamoun, L. (2015). WBAN data scheduling andaggregation under WBAN/WLAN healthcare network. Ad Hoc Networks, 25(PA), 251262.https://doi.org/10.1016/j.adhoc.2014.10.017Bradai, N., Charfi, E., Fourati, L. C., & Kamoun, L. (2016). Priority consideration ininter-WBAN data scheduling and aggregation for monitoring systems. Transactions on Emerging Telecommunications Technologies, 27(4), 589600.https://doi.org/10.1002/ett.2995Bres, A., Martnez-miranda, J., Fuster-, E., & Garca-gmez, J. M. (2015). Author s AcceptedManuscript A Novel Approach to Improve the Planning of Adaptive and Interactive Sessions for thetreatment of Major Depression Reference : Journal of Human Computer Studies, 87, 8091.https://doi.org/10.1016/j.ijhcs.2015.11.003Brunetti, N. D., De Gennaro, L., Dellegrottaglie, G., Di Giuseppe, G., Antonelli, G., & DiBiase, M. (2014). All for one, one for all: Remote telemedicine hub pre-hospitaltriage for public Emergency Medical Service 1-1-8 in a regional network forprimary PCI in Apulia, Italy. European Research in Telemedicine, 3(1), 915.https://doi.org/10.1016/j.eurtel.2013.11.001Brunetti, N. D., Scalvini, S., Acquistapace, F., Parati, G., Volterrani, M., Fedele, F., &Molinari, G. (2016). Corrigendum to ?Telemedicine for cardiovascular disease continuum: Aposition paper from the Italian Society of Cardiology Working Group on Telecardiology and Informatics? [Int J Cardiol 184 (2015) 452-458]. International Journal of Cardiology, 215, 546.https://doi.org/10.1016/j.ijcard.2016.04.160Buchmueller, T. C., Jacobson, M., & Wold, C. (2006). How far to the hospital?. Theeffect of hospital closures on access to care. Journal of Health Economics, 25(4),740761. https://doi.org/10.1016/j.jhealeco.2005.10.006Busse, R., Schreygg, J., & Smith, P. C. (2008). Variability in healthcare treatment costs amongstnine eu countries - Results from the healthbasket project. Health Economics,17(SUPPL. 1), S1S8. https://doi.org/10.1002/hec.1330ali?kan, H. (2013). Selection of boron based tribological hard coatings using multi-criteria decision making methods. Materials and Design, 50, 742749.https://doi.org/10.1016/j.matdes.2013.03.059Calyam, P., Mishra, A., Antequera, R. B., Chemodanov, D., Berryman, A., Zhu, K., Skubic, M.(2016). Synchronous Big Data analytics for personalized and remote physical therapy. Pervasive and Mobile Computing, 28, 320.https://doi.org/10.1016/j.pmcj.2015.09.004Cardellini, V., Colajanni, M., & Yu, P. S. (1999). Dynamic load balancing on web-server systems. IEEE Internet Computing, 3(3), 2839.https://doi.org/10.1109/4236.769420Cassar, K., Godden, D. J., & Duncan, J. L. (2001). Community mortality after ruptured abdominalaortic aneurysm is unrelated to the distance from the surgical centre. British Journalof Surgery, 88(10), 13411343. https://doi.org/10.1046/j.0007- 1323.2001.01877.xChakraborty, S., Ghosh, S. K., Jamthe, A., & Agrawala, D. P. (2013). Detecting mobility formonitoring patients with Parkinsons disease at home using RSSI in a wireless sensor network. Procedia Computer Science, 19, 956961.https://doi.org/10.1016/j.procs.2013.06.132Chan, M., Estve, D., Fourniols, J. Y., Escriba, C., & Campo, E. (2012). Smart wearable systems:Current status and future challenges. Artificial Intelligence in Medicine, 56(3), 137156.https://doi.org/10.1016/j.artmed.2012.09.003Chang, M.-Y., Pang, C., Michael Tarn, J., Liu, T.-S., & Yen, D. C. (2015). Exploringuser acceptance of an e-hospital service: An empirical study in Taiwan. Computer Standards &Interfaces, 38, 3543. https://doi.org/10.1016/j.csi.2014.08.004Chen, S.-J., & Hwang, C.-L. (1992). Fuzzy Multiple Attribute Decision Making Methods. In Fuzzy multiple attribute decision making (pp. 289486). Springer.https://doi.org/10.1007/978-3-642-46768-4_5Chiang, H. P., Lai, C. F., & Huang, Y. M. (2014). A green cloud-assisted healthmonitoring service on wireless body area networks. Information Sciences, 284, 118129. https://doi.org/10.1016/j.ins.2014.07.013Chowdhury, M., Mciver, W., & Light, J. (2012). Data association in remote healthmonitoring systems. IEEE Communications Magazine, 50(6), 144149.https://doi.org/10.1109/MCOM.2012.6211499Christensen, D., Jensen, N. M., Maale, R., Rudolph, S. S., Belhage, B., & Perrild, H. (2011a).Low compliance with a validated system for emergency department triage. Danish Medical Bulletin, 58(6), A4294. Retrieved fromhttp://www.ncbi.nlm.nih.gov/pubmed/21651880Christensen, D., Jensen, N. M., Maale, R., Rudolph, S. S., Belhage, B., & Perrild, H. (2011b).Nurse-administered early warning score system can be used for emergency department triage. Danish Medical Bulletin, 58(6), A4221. https://doi.org/DMBA4221[pii]Clark, R. A., Inglis, S. C., McAlister, F. A., Cleland, J. G. F., & Stewart, S.(2007). Telemonitoring or structured telephone support programmes for patients withchronic heart failure: Systematic review and meta-analysis. British Medical Journal, 334(7600),942945. https://doi.org/10.1136/bmj.39156.536968.55Clohessy, S., & Ehlers, A. (1999). PTSD symptoms and coping in ambulance serviceworkers. British Journal of Clinical Psychology, 38(3), 32.Cox, I., Roberts, L., & Stevens, S. (2002). How can we improve patient care? Community Eye Health /International Centre for Eye Health, 15(41), 13.De Backere, F., Bonte, P., Verstichel, S., Ongenae, F., & De Turck, F. (2017). TheOCarePlatform: A context-aware system to support independent living. Computer Methods and Programs in Biomedicine, 140, 111120.https://doi.org/10.1016/j.cmpb.2016.11.008De La Piedra, A., Braeken, A., Touhafi, A., & Wouters, K. (2013). Secure event logging in sensornetworks. Computers and Mathematics with Applications, 65(5), 762773.https://doi.org/10.1016/j.camwa.2012.06.019De Silva, A. H. T. E. H. T. E., Sampath, W. H. P. H. P., Sameera, N. H. L. H.L.,Amarasinghe, Y. W. R. W. R., & Mitani, A. (2018). Development of a novel telecaresystem, integrated with plantar pressure measurement system. Informatics in MedicineUnlocked, 12, 98105. https://doi.org/10.1016/j.imu.2018.07.001De Souza, V. C., & Strachan, D. P. (2005). Relationship between travel time to thenearest hospital and survival from ruptured abdominal aortic aneurysms: Record linkage study. Journal of Public Health, 27(2), 165170.https://doi.org/10.1093/pubmed/fdi001Derlet, R. W., Kinser, D., Ray, L., Hamilton, B., & McKenzie, J. (1995). ProspectiveIdentification and Triage of Nonemergency Patients Out of an EmergencyDepartment: A 5-Year Study. Annals of Emergency Medicine, 25(2), 215223.https://doi.org/10.1016/S0196-0644(95)70327-6Diaby, V., Campbell, K., & Goeree, R. (2013). Multi-criteria decision analysis (MCDA) in healthcare: A bibliometric analysis. Operations Research for Health Care, 2(1 2), 2024.https://doi.org/10.1016/j.orhc.2013.03.001Diallo, O., Rodrigues, J. J. P. C., & Sene, M. (2012). Real-time data management onwireless sensor networks: A survey. Journal of Network and Computer Applications,35(3), 10131021. https://doi.org/10.1016/j.jnca.2011.12.006Dolan, J. G., Boohaker, E., Allison, J., & Imperiale, T. F. (2013). Patients preferencesand priorities regarding colorectal cancer screening. Medical Decision Making, 33(1),5970. https://doi.org/10.1177/0272989X12453502Dong, J., & Yang, G.-H. (2015). Reliable State Feedback Control of TS Fuzzy Systems With SensorFaults. IEEE Transactions on Fuzzy Systems, 23(2), 421433.https://doi.org/10.1109/TFUZZ.2014.2315298Doumbouya, M. B., Kamsu-Foguem, B., Kenfack, H., & Foguem, C. (2014).Telemedicine using mobile telecommunication: Towards syntactic interoperability in teleexpertise. Telematics and Informatics, 31(4), 648659.https://doi.org/10.1016/j.tele.2014.01.003Doumbouya, M. B., Kamsu-Foguem, B., Kenfack, H., & Foguem, C. (2015). Aframework for decision making on teleexpertise with traceability of the reasoning. Irbm, 36(1),4051. https://doi.org/10.1016/j.irbm.2014.09.002Duke, J. M., & Aull-hyde, R. (2002). Identifying public preferences for land preservation using theanalytic hierarchy process. Ecological Economics, 42(1), 131145.Duong-Ba, T., Nguyen, T., Bose, B., & Tran, D. A. (2014). Distributed client-serverassignment for online social network applications. IEEE Transactions on Emerging Topics inComputing, 2(4), 422435. https://doi.org/10.1109/TETC.2014.2358801Durisko, C., McCue, M., Doyle, P. J., Dickey, M. W., & Fiez, J. A. (2016). A Flexible andIntegrated System for the Remote Acquisition of Neuropsychological Data in Stroke Research. Telemedicine and E-Health, 22(12), 10321040.https://doi.org/10.1089/tmj.2015.0235Elhadj, H. Ben, Elias, J., Chaari, L., & Kamoun, L. (2015). A Priority based Cross Layer Routing Protocol for healthcare applications. Ad Hoc Networks, 42.https://doi.org/http://dx.doi.org/10.1016/j.adhoc.2015.10.007Faiola, A., & Holden, R. J. (2017). Consumer Health Informatics: Empowering Healthy- Living-SeekersThrough mHealth. Progress in Cardiovascular Diseases, 59(5), 479486.https://doi.org/10.1016/j.pcad.2016.12.006Fan, X., Du, F., Guo, J., & Zhang, J. (2014). Energy independent clustering routingalgorithm for wireless sensor networks. 11th International Conference on Fuzzy Systems andKnowledge Discovery. https://doi.org/10.1109/FSKD.2014.6980948Farrohknia, N., Castrn, M., Ehrenberg, A., Lind, L., Oredsson, S., Jonsson, H., Gransson, K. E. (2011). Emergency Department Triage Scales and Their Components: A Systematic Review of the Scientific Evidence. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, 19(1), 42.https://doi.org/10.1186/1757-7241-19-42Faulin, J., Juan, A. A., Grasman, S. E., & Fry, M. J. (2012). Decision Making in ServiceIndustries: A Practical Approach. CRC Press.Fezari, M., Rasras, R., & Emary, I. M. M. E. (2015). Ambulatory Health MonitoringSystem Using Wireless Sensors Node. Procedia Computer Science, 65(Iccmit), 86 94.https://doi.org/10.1016/j.procs.2015.09.082Figueredo, M. V. M., & Dias, J. S. (2004). Mobile Telemedicine System for Home Care and PatientMonitoring. Engineering in Medicine and Biology Society, 2004. IEMBS?04. 26th Annual International Conference of the IEEE, 2, 33873390.https://doi.org/10.1109/iembs.2004.1403951Fitzgerald, J. D., Soohoo, N. F., Losina, E., & Katz, J. N. (2012). Potential impactonpatient residence to hospital travel distance and access to care under a policy ofpreferential referral to high-volume knee replacement hospitals. Arthritis Care and Research,64(6), 890897. https://doi.org/10.1002/acr.21611Fourati, H., Idoudi, H., Val, T., Van Den Bossche, A., & Saidane, L. A. (2016).Performance evaluation of IEEE 802.15.6 CSMA/CA-based CANet WBAN. Proceedings ofIEEE/ACS International Conference on Computer Systems and Applications, AICCSA.https://doi.org/10.1109/AICCSA.2015.7507181Fraile, J. A., Bajo, J., Corchado, J. M., & Abraham, A. (2010). Applying wearablesolutions in dependent environments. IEEE Transactions on InformationTechnology in Biomedicine, 14(6), 14591467. https://doi.org/10.1109/TITB.2010.2053849Fratini, A., & Caleffi, M. (2014). Medical emergency alarm dissemination in urbanenvironments. Telematics and Informatics, 31(3), 511517.https://doi.org/10.1016/j.tele.2013.11.007Frcpc, R. B., John, S., Brunswick, N., Rn, L. J., Bn, N. S., Msa, R. N., Ontario, L. (1998).Implementation Guidelines for The Canadian Emergency Department Triage & Acuity Scale ( CTAS). Canadian ED Triage & Acuity Scale. Canadian ED Triage & Acuity Scale, 32.Gambhir, S. (2016). DWBAN : Dynamic Priority based WBAN Architecture forHealthcare System. 2016 3rd International Conference on Computing for SustainableGlobal Development (INDIACom), 06.Ganapathy, K., Priya, B., Priya, B., Dhivya, A., Prashanth, V., & Vaidehi, V. (2013).SOA framework for geriatric remote health care using wireless sensor network. Procedia Computer Science, 19(Fams), 10121019.https://doi.org/10.1016/j.procs.2013.06.141Ganapathy, K., Vaidehi, V., Kannan, B., & Murugan, H. (2014). Hierarchical ParticleSwarm Optimization with Ortho-Cyclic Circles. Expert Systems with Applications, 41(7), 34603476.https://doi.org/10.1016/j.eswa.2013.10.050Ganz, A., Schafer, J. M., Tang, J., Yang, Z., Yi, J., & Ciottone, G. (2015). Urban Search andRescue Situational Awareness using DIORAMA Disaster Management System. Procedia Engineering, 107,349356. https://doi.org/10.1016/j.proeng.2015.06.091Gao, T., Massey, T., Selavo, L., Crawford, D., Chen, B. R., Lorincz, K., Welsh, M. (2007). Theadvanced health and disaster aid network: A light-weight wireless medical system for tiage.IEEE Transactions on Biomedical Circuits and Systems, 1(3), 203216.https://doi.org/10.1109/TBCAS.2007.910901Gaynor, M., & Waterman, J. (2016). Design framework for sensors and RFID tags with healthcare applications. Health Policy and Technology, 5(4), 357369.https://doi.org/10.1016/j.hlpt.2016.07.007Gbanie, S. P., Tengbe, P. B., Momoh, J. S., Medo, J., & Kabba, V. T. S. (2013).Modelling landfill location using Geographic Information Systems (GIS) and Multi- Criteria DecisionAnalysis (MCDA): Case study Bo, Southern Sierra Leone. Applied Geography, 36(January), 312.https://doi.org/10.1016/j.apgeog.2012.06.013Gehr, C. R., Von Behren, P. D., Williams, M. P., & Wood, R. B. (1998, October).Dynamic server switching for maximum server availability and load balancing.Google Patents.Georgopoulos, V. C., & Stylios, C. D. (2013). Fuzziness and Medicine: PhilosophicalReflections and Application Systems in Health Care. In R. Seising & M. E. Tabacchi(Eds.), Fuzziness and Medicine: Philosophical Reflections and Application Systems in Health Care(Vol. 302, pp. 415436). Berlin: Springer Berlin Heidelberg.https://doi.org/10.1007/978-3-642-36527-0Ghanavati, S., Abawaji, J., & Izadi, D. (2015). A Congestion Control Scheme Based on Fuzzy Logicin Wireless Body Area Networks. In 2015 IEEE 14th International Symposium on Network Computing and Applications (pp. 235242). IEEE. https://doi.org/10.1109/NCA.2015.38Ghanavati, S., Abawajy, J., & Izadi, D. (2016). ECG rate control scheme in pervasivehealth care monitoring system. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 22652270). IEEE. https://doi.org/10.1109/FUZZ- IEEE.2016.7737975Godfrey, B., et al. (2000). Emergency Medical Guidelines. Sunshine Act of Florida(Third Edit). Sunshine Act of Florida.Gogan, J. L., Davidson, E. J., & Proudfoot, J. (2016). The HealthCare.gov project.Journal of Information Technology Teaching Cases, 6(2), 99110.https://doi.org/10.1057/jittc.2016.2Gmez, J., Oviedo, B., & Zhuma, E. (2016). Patient Monitoring System Based on Internet of Things. Procedia Computer Science, 83(Ant), 9097.https://doi.org/10.1016/j.procs.2016.04.103Grossmann, F. F., Delport, K., & Keller, D. I. (2009). Emergency Severity Index. Notfall+ Rettungsmedizin, 12(4), 290292. https://doi.org/10.1007/s10049-009-1156-7 Guindo, L. A.,Wagner, M., Baltussen, R., Rindress, D., van Til, J., Kind, P., &Goetghebeur, M. M. (2012). From efficacy to equity: Literature review of decision criteria forresource allocation and healthcare decisionmaking. Cost Effectiveness and ResourceAllocation, 10(1), 9. https://doi.org/10.1186/1478-7547-10-9Gunasekaran, S., & Suresh, M. (2014). A novel control of disaster protection (NCDP) for pilgrims by pan technology. In 2014 IEEE 8th International Conference on IntelligentSystems and Control: Green Challenges and Smart Solutions, ISCO 2014- Proceedings (pp. 103107). IEEE. https://doi.org/10.1109/ISCO.2014.7103927 Gndo?du, K., &alhan, A. (2016). An Implementation of Wireless Body AreaNetworks for Improving Priority Data Transmission Delay. Journal of Medical Systems,40(3), 17. https://doi.org/10.1007/s10916-016-0443-3Haque, S. A., & Aziz, S. M. (2013). False Alarm Detection in Cyber-physical Systems for Healthcare Applications. AASRI Procedia, 5, 5461.https://doi.org/10.1016/j.aasri.2013.10.058Haralambopoulos, D. A., & Polatidis, H. (2003). Renewable energy projects: structuring amulti-criteria group decision-making framework. Renewable Energy, 28(6), 961 973.Harper, R. E., Salapura, V., & Viswanathan, M. (2017, March). Automatic management of serverfailures. Google Patents.Hedin, D. S., Kollmann, D. T., Gibson, P. L., Riehle, T. H., & Seifert, G. J.(2014).Distance bounded energy detecting ultra-wideband impulse radio secure protocol. In2014 36th Annual International Conference of the IEEE Engineering in Medicineand Biology Society, EMBC 2014 (Vol. 2014, pp. 66196622). IEEE.https://doi.org/10.1109/EMBC.2014.6945145Hermens, H., op den Akker, H., Tabak, M., Wijsman, J., & Vollenbroek, M. (2014).Personalized Coaching Systems to support healthy behavior in people with chronic conditions. Journal of Electromyography and Kinesiology, 24(6), 815826.https://doi.org/10.1016/j.jelekin.2014.10.003Hilgerink, M. P., Hummel, M. J. M., Manohar, S., Vaartjes, S. R., & Ijzerman, M. J.(2011). Assessment of the added value of the Twente Photoacoustic Mammoscope in breast cancerdiagnosis. Medical Devices: Evidence and Research, 4(1), 107115.https://doi.org/10.2147/MDER.S20169Hindia, M. N., Rahman, T. A., Ojukwu, H., Hanafi, E. B., & Fattouh, A. (2016).Enabling remote health-caring utilizing IoT concept over LTE-femtocell networks. PLoS ONE, 11(5),e0155077. https://doi.org/10.1371/journal.pone.0155077Ho, W. (2008). Integrated analytic hierarchy process and its applications - A literaturereview. European Journal of Operational Research, 186(1), 211228.https://doi.org/10.1016/j.ejor.2007.01.004Https://bestdoctors.com/. (n.d.). Retreved From.Hu, L., Zhang, Y., Feng, D., Hassan, M. M., Alelaiwi, A., & Alamri, A. (2015). Design of QoS-AwareMulti-Level MAC-Layer for Wireless Body Area Network. Journal of Medical Systems, 39(12), 192.https://doi.org/10.1007/s10916-015-0336-xHu, P. F., Yang, S., Li, H. C., Stansbury, L. G., Yang, F., Hagegeorge, G., Mackenzie,C. F. (2017). Reliable Collection of Real-Time Patient Physiologic Data from less ReliableNetworks: a ?Monitor of Monitors? System (MoMs). Journal of Medical Systems, 41(1), 3.https://doi.org/10.1007/s10916-016-0648-5Hummel, M. J. M., Volz, F., van Manen, J. G., Danner, M., Dintsios, C.-M., IJzerman,M. J., & Gerber, A. (2012). Using the Analytic Hierarchy Process to Elicit Patient Preferences.The Patient: Patient-Centered Outcomes Research, 5(4), 225237.https://doi.org/10.1007/BF03262495Hung, C., Chang, P., & Huang, Y. (2005). Comparison of Fuzzy-based MCDM and Non- fuzzy MCDM inSetting a New Fee Schedule for Orthopedic Procedures in Taiwan s National Health InsuranceProgram. WSEAS Transactions on Mathematics, 2005(1), 281285.Hussain, A., Wenbi, R., Da Silva, A. L., Nadher, M., & Mudhish, M. (2015). Health andemergency-care platform for the elderly and disabled people in the Smart City. Journal of Systems and Software, 110, 253263.https://doi.org/10.1016/j.jss.2015.08.041Hussain, M., Zaidan, A. A., Zidan, B. B., Iqbal, S., Ahmed, M. M., Albahri, O. S.,& Albahri, A. S. (2018, March). Conceptual framework for the security of mobile health applications on Android platform. Telematics and Informatics.https://doi.org/10.1016/j.tele.2018.03.005Hwang, C.-L., & Yoon, K. (1981). Multiple Attribute Decision Methods andApplications. 2011.Hwang, T. H., Kim, D. S., & Kim, J. G. (2013). An on-time power-aware schedulingscheme for medical sensor SoC-based WBAN systems. Sensors (Switzerland),13(1), 375392. https://doi.org/10.3390/s130100375Iftikhar, M., & Ahmad, I. (2014). A novel analytical model for provisioning QoS in bodyarea sensor networks. Procedia Computer Science, 32, 900907.https://doi.org/10.1016/j.procs.2014.05.509Iftikhar, M., Elaiwi, N. A. I., & Aksoy, M. S. (2014). Performance analysis of priority queuingmodel for low power Wireless Body Area Networks (WBANs). Procedia Computer Science, 34, 518525.https://doi.org/10.1016/j.procs.2014.07.060Jadhav, A., & Sonar, R. (2009). Analytic Hierarchy Process (AHP), Weighted Scoring Method(WSM), and Hybrid Knowledge Based System (HKBS) for Software Selection: A ComparativeStudy. In 2009 Second International Conference on Emerging Trends in Engineering & Technology (pp. 991997). IEEE. https://doi.org/10.1109/ICETET.2009.33J?drkiewicz, R., Tsakovski, S., Lavenu, A., Namie?nik, J., & Tobiszewski, M. (2018).Simultaneous grouping and ranking with combination of SOM and TOPSIS for selection ofpreferable analytical procedure for furan determination in food. Talanta, 178, 928933.https://doi.org/10.1016/j.talanta.2017.10.044Jeong, S., Youn, C. H., Shim, E. B., Kim, M., Cho, Y. M., & Peng, L. (2012). Anintegrated healthcare system for personalized chronic disease care in home-hospital environments.IEEE Transactions on Information Technology in Biomedicine, 16(4), 572585.https://doi.org/10.1109/TITB.2012.2190989Jin, X., Liu, H. H., Gandhi, R., Kandula, S., Mahajan, R., Zhang, M., Wattenhofer, R. (2014).Dynamic scheduling of network updates. In ACM SIGCOMM Computer Communication Review (Vol. 44, pp. 539550). ACM.https://doi.org/10.1145/2740070.2626307Johnson Colin, D., & Taylor, I. (2010). Recent Advances in Surgery 33 (Vol. 27). CRC Press.https://doi.org/10.5005/jp/books/11221Kaiser Foundation. (2007). Trends in Health Care Costs and Spending. kasir familyfoundation.Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., Albahri, O. S., & Albahri, A.S. (2018). Based on Real Time Remote Health Monitoring Systems: A New Approach for Prioritization?Large Scales Data? Patients with Chronic Heart Diseases Using Body Sensors and CommunicationTechnology. Journal of Medical Systems, 42(4), 69. https://doi.org/10.1007/s10916-018-0916-7Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., & Muzammil, H. (2018a). BasedReal Time Remote Health Monitoring Systems: A Review on Patients Prioritization and Related?Big Data? Using Body Sensors information and Communication Technology. Journal of Medical Systems, 42(2). https://doi.org/10.1007/s10916-017-0883-4Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., & Muzammil, H. (2018b). BasedReal Time Remote Health Monitoring Systems: A Review on Patients Prioritization and Related?Big Data? Using Body Sensors information and Communication Technology. Journal of Medical Systems, 42(2), 30. https://doi.org/10.1007/s10916-017-0883-4Kamsu-Foguem, B., Tchuent-Foguem, G., & Foguem, C. (2014). Conceptual graphoperations for formal visual reasoning in the medical domain. IRBM, 35(5), 262270. https://doi.org/10.1016/j.irbm.2014.04.001Kandakoglu, A., Celik, M., & Akgun, I. (2009). A multi-methodological approach forshipping registry selection in maritime transportation industry. Mathematical and ComputerModelling, 49(34), 586597. https://doi.org/10.1016/j.mcm.2008.09.001Kao, D. P., Lindenfeld, J., Macaulay, D., Birnbaum, H. G., Jarvis, J. L., Desai, U. S., & Page, R.L. (2016). Impact of a Telehealth and Care Management Program on All- Cause Mortality and Healthcare Utilization in Patients with Heart Failure. Telemedicine and E-Health,22(1), 211. https://doi.org/10.1089/tmj.2015.0007Kateretse, C., Lee, G.-W., & Huh, E.-N. (2013). A Practical Traffic Scheduling Scheme forDifferentiated Services of Healthcare Systems on Wireless Sensor Networks. Wireless Personal Communications, 71(2), 909927.https://doi.org/10.1007/s11277-012-0851-8Katib, A., Rao, D., Rao, P., Williams, K., & Grant, J. (2015). A prototype of a novel cell phone application for tracking the vaccination coverage of children in ruralcommunities. Computer Methods and Programs in Biomedicine, 122(2), 215228.https://doi.org/10.1016/j.cmpb.2015.08.008Kaur, J., Saini, K. S., & Grewal, R. (2015). Priority based congestion avoidance hybrid scheme forWireless Sensor Network. In 2015 1st International Conference on Next Generation Computing Technologies (NGCT) (pp. 158165). IEEE.https://doi.org/10.1109/NGCT.2015.7375104Keeney, R. L., & Raiffa, H. (1976). Decisions With Multiple Objectives: Preference and ValueTradeoffs. Cambridge university press.Khan, A. M. R., Prasad, P. N., & Rajamanoharane, S. (2010). A decision-making frameworkfor service quality measurements in hospitals. International Journal of Enterprise Network Management, 4(1), 80.https://doi.org/10.1504/IJENM.2010.034478Khelil, A. (2011). Pa2Pa: Patient to patient communication for emergency responsesupport. 2011 IEEE 13th International Conference on E-Health Networking,Applications and Services, HEALTHCOM 2011.https://doi.org/10.1109/HEALTH.2011.6026755Kim, H. K. (2014). Convergence agent model for developing u-healthcare systems. Future Generation Computer Systems, 35, 3948.https://doi.org/10.1016/j.future.2013.10.025Kim, K., Kyung, T., Kim, W., Shin, C., Song, Y., Lee, M. Y., Cho, Y. (2009).Efficient Management Design for Swimming Exercise Treatment. The Korean Journal of Physiology and Pharmacology, 13(6), 497.https://doi.org/10.4196/kjpp.2009.13.6.497Kim, R. H., & Kim, P. S. (2015). An Effect of Delay Reduced MAC Protocol for WBAN based MedicalSignal Monitoring, 434437.Kim, W., Han, S. K., Oh, K. J., Kim, T. Y., Ahn, H., & Song, C. (2010). The dualanalytic hierarchy process to prioritize emerging technologies. TechnologicalForecasting and Social Change, 77(4), 566577. https://doi.org/10.1016/j.techfore.2009.12.008Kitamura, Y. (2010). Decision-making process of patients with gynecological cancerregarding their cancer treatment choices using the analytic hierarchy process. JapanJournal of Nursing Science, 7(2), 148157. https://doi.org/10.1111/j.1742-7924.2010.00147.xKlersy, C., De Silvestri, A., Gabutti, G., Regoli, F., & Auricchio, A. (2009). AMeta- Analysis of Remote Monitoring of Heart Failure Patients. Journal of the American College of Cardiology, 54(18), 16831694.https://doi.org/10.1016/j.jacc.2009.08.017Kormanyos, B., & Pataki, B. (2013). Multilevel simulation of daily activities: Why and how? In2013 IEEE International Conference on Computational Intelligence and Virtual Environmentsfor Measurement Systems and Applications (CIVEMSA) (pp. 16). IEEE.https://doi.org/10.1109/CIVEMSA.2013.6617386Kovalchuk, S. V., Krotov, E., Smirnov, P. A., Nasonov, D. A., & Yakovlev, A. N.(2018). Distributed data-driven platform for urgent decision making in cardiological ambulance control. Future Generation Computer Systems, 79, 144154.https://doi.org/10.1016/j.future.2016.09.017Kumar, N., Kaur, K., Jindal, A., & Rodrigues, J. J. P. C. (2015). Providing healthcareservices on-the-fly using multi-player cooperation game theory in Internet of Vehicles(IoV) environment. Digital Communications and Networks, 1(3), 191203.https://doi.org/10.1016/j.dcan.2015.05.001Labovitz, C., Malan, G. R., & Jahanian, F. (1998). Internet Routing Instability -Networking, IEEE/ACM Transactions on. IEEE/ACM Transactions on Networking, 6(5), 515527.Lahby, M., Cherkaoui, L., & Adib, A. (2013). A novel ranking algorithm based network selection forheterogeneous wireless access. Journal of Networks, 8(2), 263272.https://doi.org/10.4304/jnw.8.2.263-272Lam, K., & Zhao, X. (1998). An application of quality function deployment to improve the quality ofteaching. International Journal of Quality & Reliability Management, 15(4), 389413.https://doi.org/10.1108/02656719810196351Lamprinakos, G. C., Asanin, S., Broden, T., Prestileo, A., Fursse, J., Papadopoulos, K. A., Venieris, I. S. (2015). An integrated remote monitoring platform towards Telehealth andTelecare services interoperability. Information Sciences, 308(March), 2337.https://doi.org/10.1016/j.ins.2015.02.032Leister, J., & Stausberg, J. (2007). Why Do Patients Select a Hospital? Journal ofHospital Marketing & Public Relations, 17(2), 1331. https://doi.org/10.1300/J375v17n02_03Leite, C. R. M., Sizilio, G. R. A., Neto, A. D. D., Valentim, R. A. M., & Guerreiro, A. M.G. (2011). A fuzzy model for processing and monitoring vital signs in ICU patients. BioMedicalEngineering Online, 10(1), 68. https://doi.org/10.1186/1475-925X-10- 68Lerner, E. B., Cone, D. C., Weinstein, E. S., Schwartz, R. B., Coule, P. L., Cronin, M., Hunt,R. C. (2011). Mass casualty triage: An evaluation of the science and refinement of a national guideline. Disaster Medicine and Public Health Preparedness, 5(2), 129137.https://doi.org/10.1001/dmp.2011.39Lesmes, D., Castillo, M., & Zarama, R. (2009). Application of the Analytic NetworkProcess (ANP) to establish weights in order to re-accredit a program of a university.In Proc. of The 10th International Symposium on The Analytic Hierarchy Process(Vol. 29).Li, C., Yuan, X., Yang, L., & Song, Y. (2015). A hybrid lifetime extended directionalapproach for WBANs. Sensors (Switzerland), 15(11), 2800528030.https://doi.org/10.3390/s151128005Li, H., & Tan, J. (2006). Body Sensor Network Based Context Aware QRS Detection. Pervasive Health Conference and Workshops, 2006, 1(2), 18.https://doi.org/10.1109/PCTHEALTH.2006.361683Li, N., Lin, K., Yong, S., Chen, X., Wang, X., & Zhang, X. (2015). Design andimplementation of a MAC protocol for a wearable monitoring system on human body. In2015 IEEE 11th International Conference on ASIC (ASICON) (pp. 14). IEEE.https://doi.org/10.1109/ASICON.2015.7517194Liaqat, T., Javaid, N., Ali, S. M., Imran, M., & Alnuem, M. (2015). Depth-based energy- balancedhybrid routing protocol for underwater WSNs. Proceedings - 2015 18th International Conference on Network-Based Information Systems, NBiS 2015.https://doi.org/10.1109/NBiS.2015.7Liberatore, M. J., & Nydick, R. L. (2008). The analytic hierarchy process in medical and healthcare decision making: A literature review. European Journal of Operational Research, 189(1),194207. https://doi.org/10.1016/j.ejor.2007.05.001Liddy, C., Dusseault, J. J., Dahrouge, S., Hogg, W., Lemelin, J., & Humbert, J. (2008).Telehomecare for patients with multiple chronic illnesses: Pilot study. Canadian FamilyPhysician, 54(1), 5865. https://doi.org/54/1/58 [pii]Ligmann-Zielinska, A., & Jankowski, P. (2012). Impact of proximity-adjustedpreferences on rank-order stability in geographical multicriteria decision analysis.Journal of Geographical Systems, 14(2), 167187. https://doi.org/10.1007/s10109- 010-0140-6Lima Junior, F. R., Osiro, L., & Carpinetti, L. C. R. (2014). A comparison between Fuzzy AHP andFuzzy TOPSIS methods to supplier selection. Applied Soft Computing Journal, 21, 194209.https://doi.org/10.1016/j.asoc.2014.03.014Lin, D., Labeau, F., Yao, Y., Vasilakos, A. V., & Tang, Y. (2016). Admission Control over Internetof Vehicles Attached with Medical Sensors for Ubiquitous Healthcare Applications. IEEE Journalof Biomedical and Health Informatics, 20(4), 1195 1204.https://doi.org/10.1109/JBHI.2015.2431744Lingsma, H. F., Steyerberg, E. W., Eijkemans, M. J. C., Dippel, D. W. J., Scholte OpReimer, W. J. M., & van Houwelingen, H. C. (2009). Comparing and ranking hospitalsbased on outcome: Results from The Netherlands Stroke Survey. Qjm, 103(2), 99108.https://doi.org/10.1093/qjmed/hcp169Liu, C. T., Long, A. G., Li, Y. C., Tsai, K. C., & Kuo, H. S. (2001). Sharing patient care recordsover the World Wide Web. International Journal of Medical Informatics, 61(23), 189205.https://doi.org/10.1016/S1386-5056(01)00141-1Liu, X., Zheng, Y., Phyu, M. W., Zhao, B., Je, M., & Yuan, X. (2011). Multiplefunctional ECG signal is processing for wearable applications of long-term cardiac monitoring. IEEE Transactions on Biomedical Engineering, 58(2), 380389.https://doi.org/10.1109/TBME.2010.2061230Lounis, A., Hadjidj, A., Bouabdallah, A., & Challal, Y. (2016). Healing on the cloud:Secure cloud architecture for medical wireless sensor networks. Future GenerationComp. Syst. 55: 266-277 (2016). Future Generation Computer Systems, 55, 266277. https://doi.org/http://dx.doi.org/10.1016/j.future.2015.01.009Lwin, M. O., Vijaykumar, S., Fernando, O. N. N., Cheong, S. A., Rathnayake, V. S.,Lim, G., Foo, S. (2014). A 21st century approach to tackling dengue:Crowdsourced surveillance, predictive mapping and tailored communication. Acta Tropica,130(1), 100107. https://doi.org/10.1016/j.actatropica.2013.09.021Malczewski, J. (1999). GIS and Multicriteria Decision Analysis. GIS, Remote Sensing, & Cartography.John Wiley & Sons. https://doi.org/10.1353/geo.2002.0003Mamoon, I. Al, Muzahidul-Islam, A. K. M., Baharun, S., Komaki, S., & Ahmed, A. (2015).Architecture and communication protocols for cognitive radio network enabled hospital. In International Symposium on Medical Information and Communication Technology, ISMICT (Vol. 2015May, pp. 170174). IEEE. https://doi.org/10.1109/ISMICT.2015.7107522Manfredi, S. (2014). Congestion control for differentiated healthcare service delivery in emerging heterogeneous wireless body area networks. IEEE Wireless Communications,21(2), 8090. https://doi.org/10.1109/MWC.2014.6812295Mani, D., & Mahendran, A. (2017). Availability modelling of fault tolerant cloudcomputing system. International Journal of Intelligent Engineering and Systems, 10(1),154165. https://doi.org/10.22266/ijies2017.0228.17MANSOOREH, M., & PET-EDWARDS, J. (1997). Technical Briefing: MakingMultiple-Objective Decisions. IEEE Computer Society Press.Mansor, H., Meskam, S. S., Zamery, N. S., Rusli, N. Q. A. M., & Akmeliawati, R.(2015). Portable heart rate measurement for remote health monitoring system. 2015 10th Asian Control Conference (ASCC), (June 2013), 15.https://doi.org/10.1109/ASCC.2015.7244405Marsh, K., Dolan, P., Kempster, J., & Lugon, M. (2013). Prioritizing investments inpublic health: A multi-criteria decision analysis. Journal of Public Health (United Kingdom),35(3), 460466. https://doi.org/10.1093/pubmed/fds099Marsh, K., Lanitis, T., Neasham, D., Orfanos, P., & Caro, J. (2014). Assessing the value ofhealthcare interventions using multi-criteria decision analysis: A review of theliterature. PharmacoEconomics, 32(4), 345365. https://doi.org/10.1007/s40273-014-0135-0Mart, R., Robles, S., Martn-Campillo, A., & Cucurull, J. (2009). Providing earlyresource allocation during emergencies: The mobile triage tag. Journal of Network and Computer Applications, 32(6), 11671182.https://doi.org/10.1016/j.jnca.2009.05.006Matin, M. (Ed.). (2012). Wireless Sensor Networks - Technology and Protocols. InTech.https://doi.org/10.5772/2604Mazomenos, E. B., Biswas, D., Acharyya, A., Chen, T., Maharatna, K., Rosengarten, J., Curzen, N. (2013). A low-complexity ECG feature extraction algorithm for mobilehealthcare applications. IEEE Journal of Biomedical and Health Informatics, 17(2), 459469.https://doi.org/10.1109/TITB.2012.2231312Meizoso, J. P., Allen, C. J., Ray, J. J., Van Haren, R. M., Teisch, L. F., Baez, X. R., Proctor,K. G. (2016). Evaluation of Miniature Wireless Vital Signs Monitor in a Trauma Intensive Care Unit. Military Medicine, 181(5S), https://doi.org/10.7205/MILMED-D-15-00162Mendes, J., Simes, H., Rosa, P., Costa, N., Rabado, C., & Pereira, A. (2013). Securelow-cost solution for elders eCardio surveillance. Procedia Computer Science, 27(Dsai2013), 4656. https://doi.org/10.1016/j.procs.2014.02.007Mendoza, G. A., & Martins, H. (2006). Multi-criteria decision analysis in naturalresource management. Forest Ecology and Management (Vol. 230). Ashgate Publishing,Ltd.Merzougui, R. (2015). Adaptation of an Intelligent Mobile Assistant Medical (IMAM) of theHeterogeneous Data for the Telemedicine Services: Design and Implementation. Wireless Personal Communications, 84(4), 30913107.https://doi.org/10.1007/s11277-015-2785-4Miah, S. J., Hasan, J., & Gammack, J. G. (2017). On-Cloud Healthcare Clinic: An e-health consultancy approach for remote communities in a developing country. Telematics and Informatics, 34(1), 311322.https://doi.org/10.1016/j.tele.2016.05.008Minutolo, A., Esposito, M., & De Pietro, G. (2015). Design and validation of a light-weight reasoning system to support remote health monitoring applications.Engineering Applications of Artificial Intelligence, 41, 232248.https://doi.org/10.1016/j.engappai.2015.01.019Mirkovic, J., Bryhni, H., & Ruland, C. (2012). A framework for the development ofubiquitous patient support systems. Proceedings of the 6th International Conference on Pervasive Computing Technologies for Healthcare.https://doi.org/10.4108/icst.pervasivehealth.2012.248594Misra, S., & Chatterjee, S. (2014). Social choice considerations in cloud-assisted WBANarchitecture for post-disaster healthcare: Data aggregation and channelization.Information Sciences, 284, 95117. https://doi.org/10.1016/j.ins.2014.05.010Misra, S., & Sarkar, S. (2015). Priority-based time-slot allocation in wireless body area networksduring medical emergency situations: An evolutionary game-theoretic perspective. IEEEJournal of Biomedical and Health Informatics, 19(2), 541548.https://doi.org/10.1109/JBHI.2014.2313374Moore, P., Thomas, A., Qassem, T., Bessis, N., & Hu, B. Monitoring Patients withMental Disorders, 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (2015).https://doi.org/10.1109/IMIS.2015.15Moreno, S., Quintero, A., Ochoa, C., Bonfante, M., Villareal, R., & Pestana, J. Remote monitoringsystem of vital signs for triage and detection of anomalous patient states in the emergencyroom, 2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016 (2016).https://doi.org/10.1109/STSIVA.2016.7743353Moretti, S., Cical, S., Mazzotti, M., Tralli, V., & Chiani, M. (2014). Content/context- awaremultiple camera selection and video adaptation for the support of m-health services. Procedia Computer Science, 40(C), 206213.https://doi.org/10.1016/j.procs.2014.12.028Moser, D. K., Kimble, L. P., Alberts, M. J., Alonzo, A., Croft, J. B., Dracup, K., Zerwic, J. J. (2006). Reducing delay in seeking treatment by patients with acutecoronary syndrome and stroke: A scientific statement from the American HeartAssociation Council on Cardiovascular Nursing and Stroke Council. Circulation,114(2), 168182. https://doi.org/10.1161/CIRCULATIONAHA.106.176040Moutacalli, M. T., Marmen, V., Bouzouane, A., & Bouchard, B. (2013). Activity pattern mining usingtemporal relationships in a smart home. In 2013 IEEE Symposium on Computational Intelligence inHealthcare and e-health (CICARE) (pp. 8387). IEEE.https://doi.org/10.1109/CICARE.2013.6583073Mhlbacher, A., & Kaczynski, A. (2016). Making good decisions in healthcare withmulti-criteria decision analysis: the use, current research and future development of MCDA. Applied Health Economics and Health Policy, 14(1), 2940.https://doi.org/10.1007/s40258-015-0203-4Murtaza, S., Al, R., & Email, W. S. (2013). QoS Taxonomy towards Wireless Body Area. International Journal of Application or Innovation in Engineering & Management(IJAIEM), 2(4), 221234.Nageba, E., Rubel, P., & Fayn, J. (2013). Towards an intelligent exploitation ofheterogeneous and distributed resources in cooperative environments of eHealth. Irbm,34(1), 7985. https://doi.org/10.1016/j.irbm.2012.12.002Negra, R., Jemili, I., & Belghith, A. (2016). Wireless Body Area Networks: Applications and Technologies. Procedia Computer Science, 83, 12741281.https://doi.org/10.1016/j.procs.2016.04.266Nguyen, T., Khosravi, A., Creighton, D., & Nahavandi, S. (2015). Medical dataclassification using interval type-2 fuzzy logic system and wavelets. Applied SoftComputing Journal, 30(4), 812822. https://doi.org/10.1016/j.asoc.2015.02.016Nicholl, J., West, J., Goodacre, S., & Turner, J. (2007). The relationship between distance tohospital and patient mortality in emergencies: An observational study. Emergency Medicine Journal,24(9), 665668. https://doi.org/10.1136/emj.2007.047654Nilsson, H., Nordstrm, E.-M., & hman, K. (2016). Decision Support for Participatory Forest Planning Using AHP and TOPSIS. Forests, 7(5), 100.https://doi.org/10.3390/f7050100Niswar, M., Ilham, A. A., Palantei, E., Sadjad, R. S., Ahmad, A., Suyuti, A., Adi.(2013). Performance evaluation of ZigBee-based wireless sensor network formonitoring patients pulse status. In 2013 International Conference on Information Technology and Electrical Engineering (ICITEE) (pp. 291294). IEEE.https://doi.org/10.1109/ICITEED.2013.6676255Niswar, M., Wijaya, A. S., Ridwan, M., Adnan, A., Ilham, A. A., Sadjad, R. S., & Vogel,A. (2015). The design of wearable medical device for triaging disaster casualties in developingcountries. In 2015 5th International Conference on Digital Information Processing and Communications, ICDIPC 2015 (pp. 207212). IEEE.https://doi.org/10.1109/ICDIPC.2015.7323030Okura, T., Enomoto, D., Miyoshi, K., Nagao, T., Kukida, M., Tanino, A., Uemura, H. (2016). TheImportance of Walking for Control of Blood Pressure: Proof Using a Telemedicine System. Telemedicine and E-Health, 22(12), 10191023. https://doi.org/10.1089/tmj.2016.0008Oliveira, M., Fontes, D. B. M. M., & Pereira, T. (2014). Multicriteria decision making: acase study in the automobile industry. Annals of Management Science, 3(1), 109.Ortz, M. A., Cmbita, J. P., La De Hoz, . A., De Felice, F., & Petrillo, A. (2016). Anintegrated approach of AHP-DEMATEL methods applied for the selection of allied hospitals inoutpatient service. International Journal of Medical Engineering and Informatics, 8(2),87107. https://doi.org/10.1504/IJMEI.2016.075760Palozzi, G., Binci, D., & Appolloni, A. (2017). e-Health and Co-production: CriticalDrivers for Chronic Diseases Management. Service Business Model Innovation in Healthcareand Hospital Management. https://doi.org/10.1007/978-3-319-46412- 1_15Paulus, A., Meisen, P., Meisen, T., Jeschke, S., Czaplik, M., & Hirsch, F. (2016).AUDIME: Augmented disaster medicine. In 2015 17th International Conference on E-Health Networking,Application and Services, HealthCom 2015 (pp. 342345). Cham: IEEE.https://doi.org/10.1109/HealthCom.2015.7454522Pawar, P., Jones, V., van Beijnum, B. J. F., & Hermens, H. (2012). A framework for the comparison of mobile patient monitoring systems. Journal of Biomedical Informatics, 45(3),544556. https://doi.org/10.1016/j.jbi.2012.02.007Pecchia, L., Bath, P. A., Pendleton, N., & Bracale, M. (2011). Analytic Hierarchy Process (AHP)for examining healthcare professionals assessments of risk factors: The relativeimportance of risk factors for falls in community-dwelling older people. Methods ofInformation in Medicine, 50(5), 435444. https://doi.org/10.3414/ME10- 01-0028Peleg, M., Shahar, Y., Quaglini, S., Broens, T., Budasu, R., Fung, N., van Schooten,B. (2017). Assessment of a personalized and distributed patient guidance system.International Journal of Medical Informatics, 101, 108130.https://doi.org/10.1016/j.ijmedinf.2017.02.010Pertet, S., Pertet, S., Narasimhan, P., & Narasimhan, P. (2005). Causes of failure in webapplications. Parallel Data Laboratory, (December), 119.Petrovic-Lazarevic, S., & Abraham, A. (2004). Hybrid Fuzzy-Linear Programming Approach forMulti Criteria Decision Making Problems. Neural, Parallel Sci. Comput., 11(1 & 2), 5368.Phillips, L., & Bana e Costa, C. (2007). Transparent priorisation, budgeting and resourceallocation with multicriteria decision analysis and decision conferencing. Annals of OperationsResearch, 154(1), 5168.Piotin, S., Benassarou, A., Blanchard, F., Nocent, O., & Bertin, E. (2013). Abdominalmorphometric data acquisition using depth sensors. In 2013 IEEE 15th International Conference one-Health Networking, Applications and Services, Healthcom 2013 (pp. 653657). IEEE.https://doi.org/10.1109/HealthCom.2013.6720757Pombo, N., Garcia, N., Felizardo, V., & Bousson, K. (2015). Big data reduction usingRBFNN: A predictive model for ECG waveform for eHealth platform integration. In 2014 IEEE 16thInternational Conference on e-Health Networking, Applications and Services, Healthcom 2014 (pp. 6670). IEEE.https://doi.org/10.1109/HealthCom.2014.7001815Puri, T., Challa, R. K., & Sehgal, N. K. (2015). Energy efficient QoS aware MAC layer time slotallocation scheme for WBASN. In 2015 International Conference on Advances in Computing,Communications and Informatics, ICACCI 2015 (pp. 966972). IEEE. https://doi.org/10.1109/ICACCI.2015.7275736Qader, M. A., Zaidan, B. B., Zaidan, A. A., Ali, S. K., Kamaluddin, M. A., & Radzi, W.B. (2017). A methodology for football players selection problem based on multi-measurements criteria analysis. Measurement: Journal of the International Measurement Confederation, 111, 3850.https://doi.org/10.1016/j.measurement.2017.07.024Qin, Y., Li, L., Zhong, X., Yang, Y., & Gwee, C. L. (2015). A Cross-Layer QoS Design with Energyand Traffic Balance Aware for Different Types of Traffic in MANETs. Wireless Personal Communications, 85(3), 14291449.https://doi.org/10.1007/s11277-015-2849-5Qu, L., & Chen, Y. (2008). A hybrid MCDM method for route selection of multimodal transportationnetwork. Lecture Notes in Computer Science (Including Subseries Lecture Notes in ArtificialIntelligence and Lecture Notes in Bioinformatics), 5263 LNCS(PART 1), 374383.https://doi.org/10.1007/978-3-540-87732-5-42Radhakrishnan, S., Duvvuru, A., & Kamarthi, S. V. (2014). Investigating Discrete Event SimulationMethod to Assess the Effectiveness of Wearable Health Monitoring Devices. Procedia Economics and Finance, 11(14), 838856.https://doi.org/10.1016/S2212-5671(14)00248-2Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., &Liljeberg, P. (2018). Exploiting smart e-Health gateways at the edge of healthcareInternet-of-Things: A fog computing approach. Future Generation Computer Systems,78(2), 641658. https://doi.org/10.1016/j.future.2017.02.014Raikhelkar, J., & Raikhelkar, J. K. (2015). The Impact of Telemedicine in CardiacCritical Care. Critical Care Clinics, 31(2), 305317. https://doi.org/10.1016/j.ccc.2014.12.008Rajan, S. P. (2015). Review and investigations on future research directions of mobilebased telecare system for cardiac surveillance. Journal of Applied Research andTechnology, 13(4), 454460. https://doi.org/10.1016/j.jart.2015.09.002Rajkumar, R., & Sriman Narayana Iyengar, N. C. (2013). Dynamic Integration of Mobile JXTA withCloud Computing for Emergency Rural Public Health Care. Osong Public Health and Research Perspectives, 4(5), 255264.https://doi.org/10.1016/j.phrp.2013.09.004Ramesh, A., & Kumar, S. (2010). Triage, monitoring, and treatment of mass casualtyevents involving chemical, biological, radiological, or nuclear agents. Journal ofPharmacy and Bioallied Sciences, 2(3), 239. https://doi.org/10.4103/0975-7406.68506Randell, B., Lee, P., & Treleaven, P. C. (1978). Reliability Issues in Computing System Design. ACM Comput. Surv., 10(2), 123165.https://doi.org/10.1145/356725.356729Rekha, R., Mathambigai, T. G., & Vidhyapriya, R. (2012). Secure Medical DataTransmission in Body Area Sensor Networks Using Dynamic Biometrics and Steganography.Bonfring International Journal of Software Engineering and Soft Computing, 2(1), 511.Ren, J., Wu, G., Li, X., Pirozmand, P., & Obaidat, M. S. (2015). Probabilistic response- timeanalysis for real-time systems in body area sensor networks. International Journal of Communication Systems, 28(16), 6.https://doi.org/10.1002/dac.2990Renner, A., Williams, R., Afb, W. P., Ganapathy, S., West, J., Weinle, N., Boswell, L.(2014). RIPPLE : Scalable Medical Telemetry System for Supporting Combat Rescue, 228232.Rezaee, A. A., Yaghmaee, M. H., & Rahmani, A. M. (2014). Optimized congestionmanagement protocol for healthcare wireless sensor networks. Wireless PersonalCommunications, 75(1), 1134. https://doi.org/10.1007/s11277-013-1337-zRezaee, A. A., Yaghmaee, M. H., Rahmani, A. M., & Mohajerzadeh, A. H. (2014). HOCA:Healthcare aware optimized congestion avoidance and control protocol for wireless sensornetworks. Journal of Network and Computer Applications, 37(1), 216228.https://doi.org/10.1016/j.jnca.2013.02.014Rezvani, S., & Ghorashi, S. A. (2013). Context aware and channel-based resourceallocation for wireless body area networks. IET Wireless Sensor Systems, 3(1), 16 25.https://doi.org/10.1049/iet-wss.2012.0100RG, R., KL, K., LB, S., K, R., & TR, P. (1984). Mood disorders in stroke patients:Importance of lesion location. Brain, 107(Pt 1), 8193.Rocha, A., Martins, A., Freire Junior, J. C., Kamel Boulos, M. N., Vicente, M. E., Feld, R., Rodriguez-Molinero, A. (2013). Innovations in health care services: the CAALYX system. Int J Med Inform, 82(11), e307-20.https://doi.org/10.1016/j.ijmedinf.2011.03.003Rodrigues, E. M. G., Godina, R., Cabrita, C. M. P., & Catalo, J. P. S. (2017).Experimental low cost reflective type oximeter for wearable health systems.Biomedical Signal Processing and Control, 31, 419433.https://doi.org/10.1016/j.bspc.2016.09.013Rodriguez, D., Heuer, S., Guerra, A., Stork, W., Weber, B., & Eichler, M. (2014).Towards automatic sensor-based triage for individual remote monitoring during mass casualtyincidents. In Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 (pp. 544551).https://doi.org/10.1109/BIBM.2014.6999217Rojahn, K., Laplante, S., Sloand, J., Main, C., Ibrahim, A., Wild, J., Johnson, K. I. (2016).Remote monitoring of chronic diseases: A landscape assessment of policies in four European countries. PLoS ONE, 11(5), 115.https://doi.org/10.1371/journal.pone.0155738Ru Kong, Chen, C., Yu, W., Yang, B., & Guan, X. (2013). Data priority based slotallocation for Wireless Body Area Networks. 2013 International Conference on Wireless Communications and Signal Processing, 16.https://doi.org/10.1109/WCSP.2013.6677273Rubio, . J., Trigo, J. D., Alesanco, ., Serrano, L., & Garca, J. (2016). Analysisof ISO/IEEE 11073 built-in security and its potential IHE-based extensibility. Journal ofBiomedical Informatics, 60, 270285. https://doi.org/10.1016/j.jbi.2016.02.006Ryu, S. (2012). Book Review: mHealth: New Horizons for Health through MobileTechnologies: Based on the Findings of the Second Global Survey on eHealth (Global Observatory for eHealth Series, Volume 3). Healthcare Informatics Research, 18(3),231. https://doi.org/10.4258/hir.2012.18.3.231Saaty, T. L. (1977). A scaling model for priorities in hierarchical structures. Journal ofMathematical Psychology, 15(3), 213281.Saaty, T. L., & Ozdemir, M. S. (2003). Why the magic number seven plus or minus two.Mathematical and Computer Modelling, 38(34), 233244.Safavi, S., & Shukur, Z. (2014). Conceptual privacy framework for health information on wearable device. PLoS ONE, 9(12), e114306.https://doi.org/10.1371/journal.pone.0114306Sakanushi, K., Hieda, T., Shiraishi, T., Ode, Y., Takeuchi, Y., Imai, M., Tanaka, H. (2013).Electronic triage system for continuously monitoring casualties at disaster scenes. Journalof Ambient Intelligence and Humanized Computing, 4(5), 547558.https://doi.org/10.1007/s12652-012-0130-2Sakr, S., & Elgammal, A. (2016). Towards a Comprehensive Data Analytics Framework for Smart Healthcare Services. Big Data Research, 4(May), 4458.https://doi.org/10.1016/j.bdr.2016.05.002Saksrisathaporn, K., Bouras, A., Reeveerakul, N., & Charles, A. (2016). Application of a DecisionModel by Using an Integration of AHP and TOPSIS Approaches within Humanitarian Operation Life Cycle. International Journal of Information Technology & Decision Making, 15(04), 887918.https://doi.org/10.1142/S0219622015500261Salatge, N., & Fabre, J. C. (2007). Fault tolerance connectors for unreliable WebServices. Proceedings of the International Conference on Dependable Systems and Networks, 5160.https://doi.org/10.1109/DSN.2007.48Saleem, K., Derhab, A., Al-Muhtadi, J., & Shahzad, B. (2015). Human-oriented design of secureMachine-to- Machine communication system for e- Healthcare society. Computers in Human Behavior, 51(NOVEMBER), 977985.https://doi.org/10.1016/j.chb.2014.10.010SALMAN, O. H. (2014). MULTI SOURCES DATA FUSION FRAMEWORK FOR REMOTE TRIAGE ANDPRIOTIRIZATION IN TELEMEDICINE. Universiti PutraMalaysia.Salman, O. H., Rasid, M. F. A., Saripan, M. I., & Subramaniam, S. K. (2014). Multi-sources data fusion framework for remote triage prioritization in telehealth. Journal of MedicalSystems, 38(9), 103. https://doi.org/10.1007/s10916-014-0103-4Salman, O. H., Zaidan, A. A., Zaidan, B. B., Naserkalid, & Hashim, M. (2017). Novel Methodologyfor Triage and Prioritizing Using ?Big Data? Patients with Chronic Heart DiseasesThrough Telemedicine Environmental. International Journal of Information Technology & Decision Making, 16(05), 12111245. https://doi.org/10.1142/S0219622017500225Sanders, T. H., Devergnas, A., Wichmann, T., & Clements, M. a. (2013). Remotesmartphone monitoring for management of Parkinsons Disease. In Proceedings of the 6thInternational Conference on PErvasive Technologies Related to Assistive Environments - PETRA ?13 (pp. 15). ACM.https://doi.org/10.1145/2504335.2504380Santos, J. R. B. Dos, Blard, G., Oliveira, A. S. R., & Carvalho, N. B. De. Wireless sensor tag andnetwork for improved clinical triage, 31 Proceedings - 18th Euromicro Conference on Digital System Design, DSD 2015 (2015).https://doi.org/10.1109/DSD.2015.66Sarkar, P., & Sinha, D. (2014). An Approach to Continuous Pervasive Care of RemotePatients Based on Priority Based Assignment of Nurse. In Lncs (Vol. 8838, pp. 327 338). Springer.https://doi.org/10.1007/978-3-662-45237-0_31Sebillo, M., Tortora, G., Tucci, M., Vitiello, G., Ginige, A., & Di Giovanni, P. (2015). Combiningpersonal diaries with territorial intelligence to empower diabetic patients. Journal of Visual Languages and Computing, 29, 114.https://doi.org/10.1016/j.jvlc.2015.03.002Sene, A., Kamsu-Foguem, B., & Rumeau, P. (2015). Telemedicine framework using case-basedreasoning with evidences. Computer Methods and Programs in Biomedicine, 121(1),2135. https://doi.org/10.1016/j.cmpb.2015.04.012Sevin, A., Bayilmis, C., & Kirbas, I. (2016). Design and implementation of a new quality of service-aware cross-layer medium access protocol for wireless body area networks. Computers and Electrical Engineering, 56, 145156.https://doi.org/10.1016/j.compeleceng.2016.02.003Shah, M. A., Kim, J., Khadra, M. H., & Feng, D. (2014). Home area network foroptimizing telehealth services-empirical simulation analysis. In 2014 36th AnnualInternational Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 (Vol. 2014, pp. 13701373). IEEE.https://doi.org/10.1109/EMBC.2014.6943854Sherekar, V., & Tatikonda, M. (2016). Impact of Factor Affecting on Labour Productivity inConstruction Projects by AHP Method. International Journal of Engineering Science andComputing, 6(6), 67716775. https://doi.org/10.4010/2016.1619Shih, D. H., Chiang, H. Sen, Lin, B., & Lin, S. Bin. (2010). An embedded mobile ECG reasoning system for elderly patients. IEEE Transactions on Information Technology in Biomedicine, 14(3), 854865.https://doi.org/10.1109/TITB.2009.2021065Shih, H. S., Shyur, H. J., & Lee, E. S. (2007). An extension of TOPSIS for groupdecision making. Mathematical and Computer Modelling, 45(78), 801813.https://doi.org/10.1016/j.mcm.2006.03.023Shnayder, V., Chen, B., Lorincz, K., Jones, T. R. F. F., & Welsh, M. (2005). Sensornetworks for medical care. Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems - SenSys ?05, 314.https://doi.org/10.1145/1098918.1098979Slotwiner, D., Varma, N., Akar, J. G., Annas, G., Beardsall, M., Fogel, R. I., Yu, C.M. (2015). HRS expert consensus statement on remote interrogation and monitoring for cardiovascularimplantable electronic devices. Heart Rhythm, 12(7), e69e100.https://doi.org/10.1016/j.hrthm.2015.05.008Smith, E., & Macdonald, R. (2006). Managing health information during disasters. The HIM Journal,35(2), 813.Smith, J., Cook, A., & Packer, C. (2010). Evaluation criteria to assess the value ofidentification sources for horizon scanning. International Journal of Technology Assessment in Health Care, 26(3), 348353.https://doi.org/10.1017/S026646231000036XSneha, S., & Varshney, U. (2013). A framework for enabling patient monitoring viamobile ad hoc network. Decision Support Systems, 55(1),https://doi.org/10.1016/j.dss.2013.01.024Sockolow, P. S., Bowles, K. H., Adelsberger, M. C., Chittams, J. L., & Liao, C. (2014).Impact of Homecare Electronic Health Record on Timeliness of ClinicalDocumentation, Reimbursement, and Patient Outcomes. Applied Clinical Informatics,5(2), 445462. https://doi.org/10.4338/ACI-2013-12-RA-0106Soto, J., Queiroz, S., & Nogueira, M. (2012). Managing sensing and cooperation toanalyze PUE attacks in Cognitive Radio Ad Hoc Networks. 2012 8Th International Conference onNetwork and Service Management (Cnsm) and 2012 Workshop on Systems Virtualiztion Management(Svm).Soufiene, B. O., Bahattab, A. A., Trad, A., & Youssef, H. (2016). Lightweight andconfidential data aggregation in healthcare wireless sensor networks. Transactions on Emerging Telecommunications Technologies, 27(4), 576588.https://doi.org/10.1002/ett.2993Steele, R., Lo, A., Secombe, C., & Wong, Y. K. (2009). Elderly persons perception and acceptanceof using wireless sensor networks to assist healthcare. International Journal of Medical Informatics, 78(12), 788801.https://doi.org/10.1016/j.ijmedinf.2009.08.001Sudha, G. F., Karthik, S., & Kumar, N. S. (2014). Activity aware energy efficient priority based multi patient monitoring adaptive system for body sensor networks. Technology andHealth Care, 22(2), 167177. https://doi.org/10.3233/THC-140782Sugeno, M., fuzzy, T. Y.-I. T. on, & 1993, undefined. (n.d.). A fuzzy-logic-basedapproach to qualitative modeling. Pdfs.Semanticscholar.Org.Sung, W. T., & Chang, K. Y. (2014). Health parameter monitoring via a novel wireless system. Applied Soft Computing Journal, 22, 667680.https://doi.org/10.1016/j.asoc.2014.04.036T. Takagi and M. Sugeno. (1985). Fuzzy identification of systems and its applications to modelingand control. In EEE Trans. Syst., Man, Cybernatics (Vol. 15, p. 116132). Elsevier.Takakuwa, K. M., Shofer, F. S., & Abbuhl, S. B. (2007). Strategies for Dealing WithEmergency Department Overcrowding: A One-Year Study on How Bedside RegistrationAffects Patient Throughput Times. Journal of Emergency Medicine, 32(4), 337342.https://doi.org/10.1016/j.jemermed.2006.07.031Tamura, T., Maeno, S., Hattori, T., Kimura, Y., Kimura, Y., Yoshida, M., & Minato, K. (2014).Assessment of participant compliance with a Web-based home healthcare system forpromoting specific health checkups. Biocybernetics and Biomedical Engineering, 34(1), 6369.https://doi.org/10.1016/j.bbe.2013.12.001Tang, D., Yu, J., Chen, X., & Makis, V. (2015). An optimal condition-based maintenance policy for adegrading system subject to the competing risks of soft and hard failure. Computers and Industrial Engineering, 83, 100110.https://doi.org/10.1016/j.cie.2015.02.003Tawfik, H., & Anya, O. (2015). Evaluating practice-centered awareness in cross- boundarytelehealth decision support systems. Telematics and Informatics, 32(3), 486503.https://doi.org/10.1016/j.tele.2014.11.002Taylan, O., Kaya, D., & Demirbas, A. (2016). An integrated multi attribute decisionmodel for energy efficiency processes in petrochemical industry applying fuzzy settheory. Energy Conversion and Management, 117, 501512.https://doi.org/10.1016/j.enconman.2016.03.048Tegegne, T., & Van Der Weide, T. P. (2014). Enriching queries with user preferences in healthcare. Information Processing and Management, 50(4), 599620.https://doi.org/10.1016/j.ipm.2014.03.004Teijeiro, T., Flix, P., Presedo, J., & Zamarrn, C. (2013). An open platform for theprotocolization of home medical supervision. Expert Systems with Applications, 40(7),26072614. https://doi.org/10.1016/j.eswa.2012.11.001Thokala, P., Devlin, N., Marsh, K., Baltussen, R., Boysen, M., Kalo, Z., Ijzerman, M. (2016).Multiple criteria decision analysis for health care decision making - An introduction:Report 1 of the ISPOR MCDA Emerging Good Practices Task Force. Value in Health, 19(1), 113.https://doi.org/10.1016/j.jval.2015.12.003Tindale, R. (2006). Paediatric triage tape. Emergency Nurse : The Journal of the RCNAccident and Emergency Nursing Association, 13(9), 6. Retrieved fromhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=prem&NEWS=N &AN=27704883Touati, F., & Tabish, R. (2013). U-healthcare system: State-of-the-art review andchallenges. Journal of Medical Systems, 37(3), 9949.https://doi.org/10.1007/s10916-013-9949-0Traverso, G., Ciccarelli, G., Schwartz, S., Hughes, T., Boettcher, T., Barman, R., Swiston, A. (2015). Physiologic status monitoring via the gastrointestinal tract. PLoSONE, 10(11). https://doi.org/10.1371/journal.pone.0141666Triantaphyllou, E. (2000). Multi-criteria Decision Making Methods: A Comparative Study. InIn Multi-criteria decision making methods: A comparative study (Vol. 44, pp. 512). Springer.https://doi.org/10.1007/978-1-4757-3157-6Triantaphyllou, E., Shu, B., Sanchez, S. N., & Ray, T. (1998). Multi-criteria decisionmaking: an operations research approach. Encyclopedia of Electrical and ElectronicsEngineering, 15(1998), 175186.Ullah, F., Khelil, A., Sheikh, A. A., Felemban, E., & Bojan, H. M. A. (2013). Towards automatedself-tagging in emergency health cases. In 2013 IEEE 15th International Conference on e-HealthNetworking, Applications and Services, Healthcom 2013 (pp. 658663). IEEE.https://doi.org/10.1109/HealthCom.2013.6720758Urovi, V., del Toro, O. J., Dubosson, F., Torres, A. R., & Schumacher, M. I. (2017).COMPOSE: Using temporal patterns for interpreting wearable sensor data with computerinterpretable guidelines. Computers in Biology and Medicine, 81, 2431.https://doi.org/10.1016/j.compbiomed.2016.11.015Vaidehi, V., Vardhini, M., Yogeshwaran, H., Inbasagar, G., Bhargavi, R., & SweetlinHemalatha, C. (2013). Agent based health monitoring of elderly people in indoorenvironments using wireless sensor networks. In Procedia Computer Science (Vol. 19, pp. 6471).https://doi.org/10.1016/j.procs.2013.06.014Valerie, B., & Stewart, T. J. (2002). Multiple Criteria Decision Analysis: An Integrated Approach.Springer Science & Business Media.van Dyk, L. (2014). A review of telehealth service implementation frameworks.International Journal of Environmental Research and Public Health, 11(2), 12791298. https://doi.org/10.3390/ijerph110201279van Til, J. A., Renzenbrink, G. J., Dolan, J. G., & IJzerman, M. J. (2008). The Use of theAnalytic Hierarchy Process to Aid Decision Making in Acquired Equinovarus Deformity.Archives of Physical Medicine and Rehabilitation, 89(3), 457462.https://doi.org/10.1016/j.apmr.2007.09.030Varshney, U. (2014). A model for improving quality of decisions in mobile health.Decision Support Systems, 62, 6677. https://doi.org/10.1016/j.dss.2014.03.005Villalonga, C., Pomares, H., Rojas, I., & Banos, O. (2017). MIMU-Wear: Ontology-based sensor selection for real-world wearable activity recognition.Neurocomputing, 250(2017), 76100. https://doi.org/10.1016/j.neucom.2016.09.125Villarreal, V., Fontecha, J., Hervas, R., & Bravo, J. (2014). Mobile and ubiquitous architecture for themedical control of chronic diseases through the use of intelligent devices: Using thearchitecture for patients with diabetes. Future GenerationComputer Systems, 34, 161175. https://doi.org/10.1016/j.future.2013.12.013Wang, J. J., Jing, Y. Y., Zhang, C. F., & Zhao, J. H. (2009). Review on multi-criteriadecision analysis aid in sustainable energy decision-making. Renewable andSustainable Energy Reviews, 13(9), 22632278. https://doi.org/10.1016/j.rser.2009.06.021Wang, J., Qiu, M., & Guo, B. (2017). Enabling real-time information service ontelehealth system over cloud-based big data platform. Journal of SystemsArchitecture, 72, 6979. https://doi.org/10.1016/j.sysarc.2016.05.003Wang, S., Hu, H., & Kingdom, U. (2012). Wireless Sensor Networks for UnderwaterLocalization : A Survey. Computer Networks, 54(15), 26882710.Wei, L., Lang, C. C., Sullivan, F. M., Boyle, P., Wang, J., Pringle, S. D., & MacDonald,T. M. (2008). Impact on mortality following first acute myocardial infarction ofdistance between home and hospital: Cohort study. Heart, 94(9), 11411146.https://doi.org/10.1136/hrt.2007.123612Westergren, H., Ferm, M., & Hggstrm, P. (2014). First evaluation of the paediatricversion of the Swedish rapid emergency triage and treatment system shows goodreliability. Acta Paediatrica, International Journal of Paediatrics, 103(3), 305308.https://doi.org/10.1111/apa.12491Whaiduzzaman, M., Gani, A., Anuar, N. B., Shiraz, M., Haque, M. N., & Haque, I. T. (2014). Cloud service selection using multicriteria decision analysis.TheScientificWorldJournal, 2014, 459375. https://doi.org/10.1155/2014/459375WHO. (2013). Surgical Care at the District Hospital. World Health Organization.WHO. (2014). [ HeRAMS ] Health Resources Availability Mapping System Greater Darfur,(June), 52.Who Organization, W. H. (2011). Disaster risk management for health fact sheets:Disaster risk management for health: Children health. Global Platform-May 2011.Widgren, B. R., & Jourak, M. (2011). Medical Emergency Triage and Treatment System (METTS): A newprotocol in primary triage and secondary priority decision in emergency medicine. Journal of Emergency Medicine, 40(6), 623628.https://doi.org/10.1016/j.jemermed.2008.04.003Wind, Y., & Saaty, T. L. (1980). Marketing Applications of the Analytic HierarchyProcess. Management Science, 26(7), 641658.https://doi.org/10.1287/mnsc.26.7.641Winkler, S., Schieber, M., Lcke, S., Heinze, P., Schweizer, T., Wegertseder, D., Koehler, F. (2011). A new telemonitoring system intended for chronic heart failure patients usingmobile telephone technology - Feasibility study. International Journal of Cardiology, 153(1),5558. https://doi.org/10.1016/j.ijcard.2010.08.038Wiseman, D. B., Ellenbogen, R., & Shaffrey, C. I. (2002). Triage for the neurosurgeon.Neurosurgical Focus, 12(3), E5. https://doi.org/120305 [pii]Wizig, L. H. (2004, May). Method and system for providing a user-selected healthcare servicespackage and healthcare services panel customized based on a users selections. GooglePatents.Woo, M. W., Lee, J. W., & Park, K. H. (2018). A reliable IoT system for PersonalHealthcare Devices. Future Generation Computer Systems, 78, 626640.https://doi.org/10.1016/j.future.2017.04.004Wood, A. (1995). Predicting client/server availability. Computer, 28(4), 4148.World Health Organization. (1996). WHO Investing in Health Research andDevelopment. Report of the Ad Hoc committee on health research relating to future interventionoptions.Xiang, Y., Liu, Z., Liu, R., Sun, W., & Wang, W. (2013). GeoSVR: A map-basedstateless VANET routing. Ad Hoc Networks, 11(7), 21252135.https://doi.org/10.1016/j.adhoc.2012.02.015Xiang, Y., & Zhuang, J. (2016). A medical resource allocation model for servingemergency victims with deteriorating health conditions. Annals of Operations Research,236(1), 177196. https://doi.org/10.1007/s10479-014-1716-1Xiao, Y., & Chen, H. (2008). Mobile telemedicine: a computing and networkingperspective. Auerbach Publications.Yaacoub, E., & Abu-dayya, A. (2012). Multihop Routing for Energy Efficiency in WirelessSensor Networks. Wireless Sensor Networks - Technology and Protocols. INTECH Open Access Publisher.Yas, Q. M., Zaidan, A. A., Zaidan, B. B., Rahmatullah, B., & Karim, H. A. (2017).Comprehensive Insights into Evaluation and Benchmarking of Real-time Skin Detectors: Review, Open Issues & Challenges, and Recommended Solutions. Measurement.Yassen, M. F., & Tarabia, A. M. K. (2017). Transient analysis of Markovian queueing system withbalking and reneging subject to catastrophes and server failures. Applied Mathematics and Information Sciences, 11(4), 10411047.https://doi.org/10.18576/amis/110410Yi, C., Alfa, A. S., & Cai, J. (2016). An Incentive-Compatible Mechanism for Transmission Scheduling of Delay-Sensitive Medical Packets in E-Health Networks. IEEE Transactions on Mobile Computing, 15(10), 24242436.https://doi.org/10.1109/TMC.2015.2500241Yi, C., Zhao, Z., Cai, J., Lobato De Faria, R., & Zhang, G. (2016). Priority-aware pricing- basedcapacity sharing scheme for beyond-wireless body area networks. Computer Networks, 98, 2943.https://doi.org/10.1016/j.comnet.2016.01.010Yoon, K., & Hwang, C.-L. (1995). Multiple attribute decision making: an introduction.Sage Publications Thousand Oaks CA (Vol. 104). Sage publications.Yuan, X., Li, C., Song, Y., Yang, L., & Ullah, S. (2015). On energy-saving in e-healthcare: A directional MAC protocol for WBAN. In 2015 IEEE GlobecomWorkshops, GC Wkshps 2015 - Proceedings (pp. 16). IEEE.https://doi.org/10.1109/GLOCOMW.2015.7414214Zachariasse, J. M., Seiger, N., Rood, P. P. M., Alves, C. F., Freitas, P., Smit, F. J., Moll, H.A. (2017). Validity of the Manchester triage system in emergency care: A prospective observational study. PLoS ONE, 12(2), e0170811.https://doi.org/10.1371/journal.pone.0170811Zaidan, A. A., Karim, H. A., Ahmad, N. N., Zaidan, B. B., & Kiah, M. L. M. (2015). RobustPornography Classification Solving the Image Size Variation Problem Based on Multi-AgentLearning. Journal of Circuits Systems and Computers, 24(2), 37.https://doi.org/10.1142/s0218126615500231Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi,M. (2015). Evaluation and selection of open-source EMR software packages based on integrated AHPand TOPSIS. Journal of Biomedical Informatics, 53, 390404.https://doi.org/10.1016/j.jbi.2014.11.012Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Albahri, A. S., Yas, Q. M., &Hashim, M. (2018). A review on smartphone skin cancer diagnosis apps in evaluation andbenchmarking: coherent taxonomy, open issues and recommendation pathway solution. Health andTechnology. https://doi.org/10.1007/s12553-018- 0223-9Zaidan, A. A., Zaidan, B. B., Qahtan, M. Y., Albahri, O. S., Albahri, A. S., Alaa, M., Lim, C.K. (2018). A survey on communication components for IoT-based technologies in smart homes. Telecommunication Systems, 69(1), 125.https://doi.org/10.1007/s11235-018-0430-8Zane, R. D., & Biddinger, P. (2011). Home Health Patient Assessment Tools: Preparing for EmergencyTriage. Abt Associates.Zanjal, S. V., & Talmale, G. R. (2016). Medicine Reminder and Monitoring System for Secure Health Using IOT. Physics Procedia, 78(December 2015), 471476.https://doi.org/10.1016/j.procs.2016.02.090Zarabzadeh, A., ODonoghue, J., OConnor, Y., OKane, T., Woodworth, S., Gallagher, J., & OConnor,S. (2013). Variation in health care providers perceptions: Decision making based on patient vitalsigns. Journal of Decision Systems, 22(3), 168189. https://doi.org/10.1080/12460125.2013.817063Zardari, N. H., Ahmed, K., Shirazi, S. M., & Yusop, Z. Bin. (2015). Weighting Methods and theirEffects on Multi-Criteria Decision Making Model Outcomes in Water Resources Management.International Journal of Operarations Research, 10(2), 5666.https://doi.org/10.1007/978-3-319-12586-2Zhang, J., Goode, K. M., Cuddihy, P. E., & Cleland, J. G. F. (2009). Predictinghospitalization due to worsening heart failure using daily weight measurement: Analysisof the Trans-European Network-Home-Care Management System (TEN- HMS) study. European Journal of Heart Failure, 11(4), 420427.https://doi.org/10.1093/eurjhf/hfp033Zhang, K., Liang, X., Baura, M., Lu, R., & Shen, X. (2014). PHDA: A priority basedhealth data aggregation with privacy preservation for cloud assisted WBANs.Information Sciences, 284, 130141. https://doi.org/10.1016/j.ins.2014.06.011Zhang, Z., Buckler, E. S., Casstevens, T. M., & Bradbury, P. J. (2009). Softwareengineering the mixed model for genome-wide association studies on large samples. Briefings in Bioinformatics (Vol. 10). IEEE Computer Society.https://doi.org/10.1093/bib/bbp050Zhao, Y., & Kerkhoff, H. G. (2014). Design of an embedded health monitoringinfrastructure for accessing multi-processor SoC degradation. In Proceedings - 2014 17th EuromicroConference on Digital System Design, DSD 2014 (pp. 154160). IEEE.https://doi.org/10.1109/DSD.2014.80Zheng, G., Ning, Y., & Wang, M. (2010). Energy efficient geography-based data forwarding algorithm for multi-hop wireless sensor network. Proceedings - InternationalConference on Electrical and Control Engineering, ICECE 2010.https://doi.org/10.1109/iCECE.2010.1263Zheng, Z., Zhang, Y., & Lyu, M. R. (2010). Distributed QoS evaluation for real-world Web services.ICWS 2010 - 2010 IEEE 8th International Conference on Web Services, 8390.https://doi.org/10.1109/ICWS.2010.10Zhu-juan, W. (2015). Emergency Treatment in Smart Terminal-based E-healthcare Networks,(Iccsnt), 11781181.Zionts, S. (1979). MCDMIf Not a Roman Numeral, Then What? Interfaces, 9(4), 94 101.https://doi.org/10.1287/inte.9.4.94Spada, E. J., & Kim, Y. (2018, May 15). Fault tolerant clock network. Google Patents.

Fault-tolerant mhealth framework in telemedicine environment for chronic heart disease patients

Similar Items