Statistical modeling for prediction of diabetes in Malaysians

Type II Diabetes Mellitus is one of the silent killer diseases worldwide. According to the World Health Organization, 347 million people are suffering from diabetes throughout the world. To overcome the sharp rise in the disease, various diagnostic or prediction models were developed through various...

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Main Authors:	Zehra, Amatul, Abdul Kadir, Tuty Asmawaty, Md Aris, Mohd Aznan, Badshah, Gran, Haq, Riaz-ul
Format:	Article
Language:	English
Published:	2018
Subjects:	R Medicine (General) RZ Other systems of medicine
Online Access:	http://irep.iium.edu.my/65987/ http://irep.iium.edu.my/65987/ http://irep.iium.edu.my/65987/1/65987_Statistical%20modeling%20for%20prediction%20of%20diabetes%20in%20Malaysians.pdf

id	iium-65987
recordtype	eprints
spelling	iium-659872018-09-05T02:05:57Z http://irep.iium.edu.my/65987/ Statistical modeling for prediction of diabetes in Malaysians Zehra, Amatul Abdul Kadir, Tuty Asmawaty Md Aris, Mohd Aznan Badshah, Gran Haq, Riaz-ul R Medicine (General) RZ Other systems of medicine Type II Diabetes Mellitus is one of the silent killer diseases worldwide. According to the World Health Organization, 347 million people are suffering from diabetes throughout the world. To overcome the sharp rise in the disease, various diagnostic or prediction models were developed through various techniques such as artificial intelligence, classification and clustering, pattern recognition and statistical methods. The study led to the related open issues of identifying the need of a relation between the major factors that lead to the development of diabetes. This is possible by investigating the links found between the independent and dependant variables in the dataset. This paper investigates the effect of binary logistic regression applied on a dataset. The results show that the most effective method was the enter method which gave a prediction accuracy of almost 93%. 2018-06 Article PeerReviewed application/pdf en http://irep.iium.edu.my/65987/1/65987_Statistical%20modeling%20for%20prediction%20of%20diabetes%20in%20Malaysians.pdf Zehra, Amatul and Abdul Kadir, Tuty Asmawaty and Md Aris, Mohd Aznan and Badshah, Gran and Haq, Riaz-ul (2018) Statistical modeling for prediction of diabetes in Malaysians. Life Science Journal, 15 (6). pp. 76-80. ISSN 1097-8135 E-ISSN 2372-613X http://www.lifesciencesite.com/lsj/life150618/09_26766lsj150618_76_80.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	R Medicine (General) RZ Other systems of medicine
spellingShingle	R Medicine (General) RZ Other systems of medicine Zehra, Amatul Abdul Kadir, Tuty Asmawaty Md Aris, Mohd Aznan Badshah, Gran Haq, Riaz-ul Statistical modeling for prediction of diabetes in Malaysians
description	Type II Diabetes Mellitus is one of the silent killer diseases worldwide. According to the World Health Organization, 347 million people are suffering from diabetes throughout the world. To overcome the sharp rise in the disease, various diagnostic or prediction models were developed through various techniques such as artificial intelligence, classification and clustering, pattern recognition and statistical methods. The study led to the related open issues of identifying the need of a relation between the major factors that lead to the development of diabetes. This is possible by investigating the links found between the independent and dependant variables in the dataset. This paper investigates the effect of binary logistic regression applied on a dataset. The results show that the most effective method was the enter method which gave a prediction accuracy of almost 93%.
format	Article
author	Zehra, Amatul Abdul Kadir, Tuty Asmawaty Md Aris, Mohd Aznan Badshah, Gran Haq, Riaz-ul
author_facet	Zehra, Amatul Abdul Kadir, Tuty Asmawaty Md Aris, Mohd Aznan Badshah, Gran Haq, Riaz-ul
author_sort	Zehra, Amatul
title	Statistical modeling for prediction of diabetes in Malaysians
title_short	Statistical modeling for prediction of diabetes in Malaysians
title_full	Statistical modeling for prediction of diabetes in Malaysians
title_fullStr	Statistical modeling for prediction of diabetes in Malaysians
title_full_unstemmed	Statistical modeling for prediction of diabetes in Malaysians
title_sort	statistical modeling for prediction of diabetes in malaysians
publishDate	2018
url	http://irep.iium.edu.my/65987/ http://irep.iium.edu.my/65987/ http://irep.iium.edu.my/65987/1/65987_Statistical%20modeling%20for%20prediction%20of%20diabetes%20in%20Malaysians.pdf
first_indexed	2023-09-18T21:33:39Z
last_indexed	2023-09-18T21:33:39Z
_version_	1777412676408836096

Statistical modeling for prediction of diabetes in Malaysians

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