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A Systematic Review of Machine Learning in Substance Addiction

Patient treatment; Healthcare industry; Machine learning methods; Open doors; Systematic Review; Machine learning

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Bibliographic Details
Main Authors: Zulkifli N.F., Cob Z.C., Latif A.A., Drus S.M.
Other Authors: 57220808082
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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id my.uniten.dspace-25352
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spelling my.uniten.dspace-253522023-05-29T16:08:26Z A Systematic Review of Machine Learning in Substance Addiction Zulkifli N.F. Cob Z.C. Latif A.A. Drus S.M. 57220808082 25824919900 46461488000 56330463900 Patient treatment; Healthcare industry; Machine learning methods; Open doors; Systematic Review; Machine learning Substance addiction affects millions of people worldwide and there is no cure for addiction. With the emergence of machine learning, it has open doors for healthcare industry to incorporate technology to help healthcare workforce to make better decision in treating patients. By applying machine learning in understanding patients with substance addiction, it can help in determining their treatment. This paper aims to provide a summary of how effective machine learning method is applied in addiction studies in which 11 studies are included in this paper by using PRISMA methodology to find sources. � 2020 IEEE. Final 2023-05-29T08:08:26Z 2023-05-29T08:08:26Z 2020 Conference Paper 10.1109/ICIMU49871.2020.9243581 2-s2.0-85097639829 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097639829&doi=10.1109%2fICIMU49871.2020.9243581&partnerID=40&md5=7542b31ea6cbd200ae7ae78a975cbdb3 https://irepository.uniten.edu.my/handle/123456789/25352 9243581 103 107 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Patient treatment; Healthcare industry; Machine learning methods; Open doors; Systematic Review; Machine learning
author2 57220808082
author_facet 57220808082
Zulkifli N.F.
Cob Z.C.
Latif A.A.
Drus S.M.
format Conference Paper
author Zulkifli N.F.
Cob Z.C.
Latif A.A.
Drus S.M.
spellingShingle Zulkifli N.F.
Cob Z.C.
Latif A.A.
Drus S.M.
A Systematic Review of Machine Learning in Substance Addiction
author_sort Zulkifli N.F.
title A Systematic Review of Machine Learning in Substance Addiction
title_short A Systematic Review of Machine Learning in Substance Addiction
title_full A Systematic Review of Machine Learning in Substance Addiction
title_fullStr A Systematic Review of Machine Learning in Substance Addiction
title_full_unstemmed A Systematic Review of Machine Learning in Substance Addiction
title_sort systematic review of machine learning in substance addiction
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806424176214409216
score 13.214268

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