Machine learning cases in clinical and biomedical domains

The aim of this paper is twofold: Firstly, to provide introductory knowledge to the reader who has little or no knowledge of machine learning with examples of applications in clinical and biomedical domains, and secondly, to compare and contrast the concept of Artificial Neural Network (ANN) and the...

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Main Authors:	Che Azemin, Mohd Zulfaezal, Ashimi, Tijani Ahmad, Md Mustafa, Md Muziman Syah
Format:	Article
Language:	English English
Published:	IIUM Press, International Islamic University Malaysia 2018
Subjects:	Q Science (General) R Medicine (General)
Online Access:	http://irep.iium.edu.my/60179/ http://irep.iium.edu.my/60179/ http://irep.iium.edu.my/60179/1/60179_Machine%20learning%20cases%20in%20clinical.pdf http://irep.iium.edu.my/60179/7/60179_Machine%20Learning%20Cases%20in%20Clinical%20and%20Biomedical%20Domains_WOS.pdf

id	iium-60179
recordtype	eprints
spelling	iium-601792020-02-26T15:15:54Z http://irep.iium.edu.my/60179/ Machine learning cases in clinical and biomedical domains Che Azemin, Mohd Zulfaezal Ashimi, Tijani Ahmad Md Mustafa, Md Muziman Syah Q Science (General) R Medicine (General) The aim of this paper is twofold: Firstly, to provide introductory knowledge to the reader who has little or no knowledge of machine learning with examples of applications in clinical and biomedical domains, and secondly, to compare and contrast the concept of Artificial Neural Network (ANN) and the Qur’anic concept of intellect (aql) in the Qur’an. Learning algorithm can generally be categorised into supervised and unsupervised learning. To better understand the machine learning concept, hypothetical data of glaucoma cases are presented. ANN is then selected as an example of supervised learning and the underlying principles in ANN are presented with general audience in mind with an attempt to relate the mechanism employed in the algorithm with Qur’anic verses containing the verbs derived from aql. The applications of machine learning in clinical and biomedical domains are briefly demonstrated based on the author’s own research and most recent examples available from University of California, Irvine Machine Learning Repository. Selected verses which indicate motivation to use the intellect in positive manners and rebuke to those who do not activate the intellect are presented. The evidence found from the verses suggests that ANN shares similar learning process to achieve belief (iman) by analysing the similitudes (amsal) introduced to the algorithm. IIUM Press, International Islamic University Malaysia 2018-07 Article PeerReviewed application/pdf en http://irep.iium.edu.my/60179/1/60179_Machine%20learning%20cases%20in%20clinical.pdf application/pdf en http://irep.iium.edu.my/60179/7/60179_Machine%20Learning%20Cases%20in%20Clinical%20and%20Biomedical%20Domains_WOS.pdf Che Azemin, Mohd Zulfaezal and Ashimi, Tijani Ahmad and Md Mustafa, Md Muziman Syah (2018) Machine learning cases in clinical and biomedical domains. International Medical Journal Malaysia, 17 (Special Issue 1). pp. 135-140. E-ISSN 1823-4631 http://iiumedic.net/imjm/v1/download/volume_17_special_issue_1/Pages-from-2WCIIv1-135-140.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	Q Science (General) R Medicine (General)
spellingShingle	Q Science (General) R Medicine (General) Che Azemin, Mohd Zulfaezal Ashimi, Tijani Ahmad Md Mustafa, Md Muziman Syah Machine learning cases in clinical and biomedical domains
description	The aim of this paper is twofold: Firstly, to provide introductory knowledge to the reader who has little or no knowledge of machine learning with examples of applications in clinical and biomedical domains, and secondly, to compare and contrast the concept of Artificial Neural Network (ANN) and the Qur’anic concept of intellect (aql) in the Qur’an. Learning algorithm can generally be categorised into supervised and unsupervised learning. To better understand the machine learning concept, hypothetical data of glaucoma cases are presented. ANN is then selected as an example of supervised learning and the underlying principles in ANN are presented with general audience in mind with an attempt to relate the mechanism employed in the algorithm with Qur’anic verses containing the verbs derived from aql. The applications of machine learning in clinical and biomedical domains are briefly demonstrated based on the author’s own research and most recent examples available from University of California, Irvine Machine Learning Repository. Selected verses which indicate motivation to use the intellect in positive manners and rebuke to those who do not activate the intellect are presented. The evidence found from the verses suggests that ANN shares similar learning process to achieve belief (iman) by analysing the similitudes (amsal) introduced to the algorithm.
format	Article
author	Che Azemin, Mohd Zulfaezal Ashimi, Tijani Ahmad Md Mustafa, Md Muziman Syah
author_facet	Che Azemin, Mohd Zulfaezal Ashimi, Tijani Ahmad Md Mustafa, Md Muziman Syah
author_sort	Che Azemin, Mohd Zulfaezal
title	Machine learning cases in clinical and biomedical domains
title_short	Machine learning cases in clinical and biomedical domains
title_full	Machine learning cases in clinical and biomedical domains
title_fullStr	Machine learning cases in clinical and biomedical domains
title_full_unstemmed	Machine learning cases in clinical and biomedical domains
title_sort	machine learning cases in clinical and biomedical domains
publisher	IIUM Press, International Islamic University Malaysia
publishDate	2018
url	http://irep.iium.edu.my/60179/ http://irep.iium.edu.my/60179/ http://irep.iium.edu.my/60179/1/60179_Machine%20learning%20cases%20in%20clinical.pdf http://irep.iium.edu.my/60179/7/60179_Machine%20Learning%20Cases%20in%20Clinical%20and%20Biomedical%20Domains_WOS.pdf
first_indexed	2023-09-18T21:25:18Z
last_indexed	2023-09-18T21:25:18Z
_version_	1777412151720280064

Machine learning cases in clinical and biomedical domains

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