Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data

In this research, I investigate and compared two of Artificial Intelligence (AI)techniques which are; Neural network and Rough set will be the best technique to be use in analyzing data. Recently, AI is one of the techniques which still in development process that produced few of intelligent system...

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Main Author:	Nur Aniza, Alang Ismail
Format:	Thesis
Language:	eng eng
Published:	2009
Subjects:	QA76 Computer software
Online Access:	https://etd.uum.edu.my/1909/1/Nur_Aniza_Bt_Alang_Ismail.pdf https://etd.uum.edu.my/1909/2/1.Nur_Aniza_Bt_Alang_Ismail.pdf
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id	my-uum-etd.1909
record_format	uketd_dc
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
topic	QA76 Computer software
spellingShingle	QA76 Computer software Nur Aniza, Alang Ismail Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data
description	In this research, I investigate and compared two of Artificial Intelligence (AI)techniques which are; Neural network and Rough set will be the best technique to be use in analyzing data. Recently, AI is one of the techniques which still in development process that produced few of intelligent systems that helped human to support their daily life such as decision making. In Malaysia, it is newly introduced by a group of researchers from University Science Malaysia. They agreed with others world-wide researchers that AI is very helpful to replaced human intelligence and do many works that can be done by human especially in medical area.In this research, I have chosen three sets of medical data; Wisoncin Prognostic Breast cancer, Parkinson’s diseases and Hepatitis Prognostic. The reason why the medical data is selected for this research because of the popularity among the researchers that done their research in AI by using medical data and the prediction or target attributes is clearly understandable. The results and findings also discussed in this paper. How the experiment has been done; the steps involved also discussed in this paper. I also conclude this paper with conclusion and future work.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Nur Aniza, Alang Ismail
author_facet	Nur Aniza, Alang Ismail
author_sort	Nur Aniza, Alang Ismail
title	Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data
title_short	Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data
title_full	Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data
title_fullStr	Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data
title_full_unstemmed	Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data
title_sort	comparing the performances of neural network and rough set theory to reflect the improvement of prognostic in medical data
granting_institution	Universiti Utara Malaysia
granting_department	College of Arts and Sciences (CAS)
publishDate	2009
url	https://etd.uum.edu.my/1909/1/Nur_Aniza_Bt_Alang_Ismail.pdf https://etd.uum.edu.my/1909/2/1.Nur_Aniza_Bt_Alang_Ismail.pdf
_version_	1747827230077091840
spelling	my-uum-etd.19092013-07-24T12:13:40Z Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data 2009 Nur Aniza, Alang Ismail College of Arts and Sciences (CAS) College of Arts and Sciences QA76 Computer software In this research, I investigate and compared two of Artificial Intelligence (AI)techniques which are; Neural network and Rough set will be the best technique to be use in analyzing data. Recently, AI is one of the techniques which still in development process that produced few of intelligent systems that helped human to support their daily life such as decision making. In Malaysia, it is newly introduced by a group of researchers from University Science Malaysia. They agreed with others world-wide researchers that AI is very helpful to replaced human intelligence and do many works that can be done by human especially in medical area.In this research, I have chosen three sets of medical data; Wisoncin Prognostic Breast cancer, Parkinson’s diseases and Hepatitis Prognostic. The reason why the medical data is selected for this research because of the popularity among the researchers that done their research in AI by using medical data and the prediction or target attributes is clearly understandable. The results and findings also discussed in this paper. How the experiment has been done; the steps involved also discussed in this paper. I also conclude this paper with conclusion and future work. 2009 Thesis https://etd.uum.edu.my/1909/ https://etd.uum.edu.my/1909/1/Nur_Aniza_Bt_Alang_Ismail.pdf application/pdf eng validuser https://etd.uum.edu.my/1909/2/1.Nur_Aniza_Bt_Alang_Ismail.pdf application/pdf eng public masters masters Universiti Utara Malaysia Cawsey, A. (1998). The essence of artificial intelligence. Prentice-Hall: England.Depolo J. (2005). Breath Easy. Futures magazine. Vol. 23, No. 2. Retrieved from http://www.worldandijournal.com.eserv.uum.edu.my/subscribers/searchdetail.asp?num=25372 Legg S. and Hutter M. (2007). Universal Intelligence: A Definition of Machine Intelligence. Mind and Machines. Volume 17 , Issue 4.Kluwer Academic Publishers, Massachusetts.Lehner P.E. (1986). On the Role of Artificial Intelligence in Command and Control. IEEE Transactions on Systems, Man, and Cybernetics, Vol. Smc-16, No. 6.Luger, G.F (2005). Artificial intelligence: structures and strategies for complex problem solving. 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Comparing the Performances of Neural Network and Rough Set Theory to Reflect the Improvement of Prognostic in Medical Data

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