Machine learning in fMRI classification

Statistical analysis method is utilitarian in neuroimaging. For instance, SPM12, FSL and BrainVoyager are widely used for testing the hypotheses about functional magnetic resonance imaging (fMRI). However, that testing and studying of brain images mostly consist of experts work. It is not fully auto...

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Main Authors:	Mohd Suhaimi, Nur Farahana, Htike@Muhammad Yusof, Zaw Zaw
Format:	Conference or Workshop Item
Language:	English
Published:	International Neuroinformatics Coordinating Facilities (INCF) 2016
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/61306/ http://irep.iium.edu.my/61306/ http://irep.iium.edu.my/61306/ http://irep.iium.edu.my/61306/6/61306-Machine%20learning.pdf

id	iium-61306
recordtype	eprints
spelling	iium-613062018-06-29T03:28:37Z http://irep.iium.edu.my/61306/ Machine learning in fMRI classification Mohd Suhaimi, Nur Farahana Htike@Muhammad Yusof, Zaw Zaw T Technology (General) Statistical analysis method is utilitarian in neuroimaging. For instance, SPM12, FSL and BrainVoyager are widely used for testing the hypotheses about functional magnetic resonance imaging (fMRI). However, that testing and studying of brain images mostly consist of experts work. It is not fully automatic and time-consuming. There are fractions of decision making processes by the experts that require extensive knowledge and sets of rule of thumb. Systematically, machine learning is expected to automate the process while running the embedded sets of rule of thumb during the process. In addition, pattern recognition is one of the method in machine learning that differ to working principle of SPM12 and its counterpart. The recognizing of patterns in brain images is expected to pragmatically tackle the work of testing the fMRI hypotheses. Thus, the aim of this paper is to prove the need of machine learning in fMRI classification. International Neuroinformatics Coordinating Facilities (INCF) 2016 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/61306/6/61306-Machine%20learning.pdf Mohd Suhaimi, Nur Farahana and Htike@Muhammad Yusof, Zaw Zaw (2016) Machine learning in fMRI classification. In: Neuroinformatics 2016, 3rd-4th September 2016, Reading, United Kingdom. https://www.frontiersin.org/books/Neuroinformatics_2016/976 10.3389/978-2-88919-953-2
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Mohd Suhaimi, Nur Farahana Htike@Muhammad Yusof, Zaw Zaw Machine learning in fMRI classification
description	Statistical analysis method is utilitarian in neuroimaging. For instance, SPM12, FSL and BrainVoyager are widely used for testing the hypotheses about functional magnetic resonance imaging (fMRI). However, that testing and studying of brain images mostly consist of experts work. It is not fully automatic and time-consuming. There are fractions of decision making processes by the experts that require extensive knowledge and sets of rule of thumb. Systematically, machine learning is expected to automate the process while running the embedded sets of rule of thumb during the process. In addition, pattern recognition is one of the method in machine learning that differ to working principle of SPM12 and its counterpart. The recognizing of patterns in brain images is expected to pragmatically tackle the work of testing the fMRI hypotheses. Thus, the aim of this paper is to prove the need of machine learning in fMRI classification.
format	Conference or Workshop Item
author	Mohd Suhaimi, Nur Farahana Htike@Muhammad Yusof, Zaw Zaw
author_facet	Mohd Suhaimi, Nur Farahana Htike@Muhammad Yusof, Zaw Zaw
author_sort	Mohd Suhaimi, Nur Farahana
title	Machine learning in fMRI classification
title_short	Machine learning in fMRI classification
title_full	Machine learning in fMRI classification
title_fullStr	Machine learning in fMRI classification
title_full_unstemmed	Machine learning in fMRI classification
title_sort	machine learning in fmri classification
publisher	International Neuroinformatics Coordinating Facilities (INCF)
publishDate	2016
url	http://irep.iium.edu.my/61306/ http://irep.iium.edu.my/61306/ http://irep.iium.edu.my/61306/ http://irep.iium.edu.my/61306/6/61306-Machine%20learning.pdf
first_indexed	2023-09-18T21:26:56Z
last_indexed	2023-09-18T21:26:56Z
_version_	1777412254615994368

Machine learning in fMRI classification

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