Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar

The problem in most of the clinics around the world is the procedure of the patient to see the doctor. Patient need to register, queuing and this will consuming time. A Mobile Fever Diagnosis Expert System (MFDES) is developed to reduce the waiting time of the patient to see doctor for a treatment....

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Main Author:	Mohd Nashrullah, Zulfakar
Format:	Thesis
Language:	English
Published:	2014
Subjects:	Neural Networks (Computer) Artificial intelligence Cell phones
Online Access:	https://ir.uitm.edu.my/id/eprint/32715/1/32715.pdf
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id	my-uitm-ir.32715
record_format	uketd_dc
spelling	my-uitm-ir.327152020-07-21T03:48:26Z Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar 2014-01-26 Mohd Nashrullah, Zulfakar Neural Networks (Computer). Artificial intelligence Cell phones The problem in most of the clinics around the world is the procedure of the patient to see the doctor. Patient need to register, queuing and this will consuming time. A Mobile Fever Diagnosis Expert System (MFDES) is developed to reduce the waiting time of the patient to see doctor for a treatment. The scope of this MFDES is for two type of fever that was the normal fever and dengue fever. This research has conducted in the Unit Kesihatan (UK) UiTM Seri Iskandar Perak. This MFDES was developed in android platform using the Visual Basic Language Programming. The MFDES is implemented through the rule-based expert system rule using IF THEN rule. The MFDES is able to diagnose fever based on the symptoms given in the system and provide recommendation of the medicine depending on disease. The results from this project MFDES has reduce time that doctor take to diagnose patient if the patient disease was fever type. The MFDES can be enhanced by adding more function, adding more type of fever and developed it into another programming language. Summary of MFDES based on finding and analysis show that MFDES diagnose faster than the manual diagnose. 2014-01 Thesis https://ir.uitm.edu.my/id/eprint/32715/ https://ir.uitm.edu.my/id/eprint/32715/1/32715.pdf text en public degree Universiti Teknologi MARA Cawangan Perak Faculty of Computer and Mathematical Sciences Bohari, Wahijan
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Bohari, Wahijan
topic	Neural Networks (Computer) Artificial intelligence Cell phones
spellingShingle	Neural Networks (Computer) Artificial intelligence Cell phones Mohd Nashrullah, Zulfakar Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar
description	The problem in most of the clinics around the world is the procedure of the patient to see the doctor. Patient need to register, queuing and this will consuming time. A Mobile Fever Diagnosis Expert System (MFDES) is developed to reduce the waiting time of the patient to see doctor for a treatment. The scope of this MFDES is for two type of fever that was the normal fever and dengue fever. This research has conducted in the Unit Kesihatan (UK) UiTM Seri Iskandar Perak. This MFDES was developed in android platform using the Visual Basic Language Programming. The MFDES is implemented through the rule-based expert system rule using IF THEN rule. The MFDES is able to diagnose fever based on the symptoms given in the system and provide recommendation of the medicine depending on disease. The results from this project MFDES has reduce time that doctor take to diagnose patient if the patient disease was fever type. The MFDES can be enhanced by adding more function, adding more type of fever and developed it into another programming language. Summary of MFDES based on finding and analysis show that MFDES diagnose faster than the manual diagnose.
format	Thesis
qualification_level	Bachelor degree
author	Mohd Nashrullah, Zulfakar
author_facet	Mohd Nashrullah, Zulfakar
author_sort	Mohd Nashrullah, Zulfakar
title	Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar
title_short	Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar
title_full	Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar
title_fullStr	Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar
title_full_unstemmed	Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar
title_sort	mobile fever diagnosis expert system / mohd nashrullah zulfakar
granting_institution	Universiti Teknologi MARA Cawangan Perak
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2014
url	https://ir.uitm.edu.my/id/eprint/32715/1/32715.pdf
_version_	1783734180675321856

Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar

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