relation: https://khub.utp.edu.my/scholars/10145/
title: Machine Learning and Stress Assessment: A Review
creator: Faraz, S.
creator: Ali, S.S.A.
creator: Adil, S.H.
description: Stress assessment has been considered essentials in the early stages because stress-related abnormalities tend to increase the risk of strokes, heart attacks, depression, and hypertension. This may also induce suicidal thought within the victims of this neurological state. The CAD (Computer Aided Diagnosis) have been a way forward for both medical experts and people with complications. The recent development of Machine learning revolution has proved to be substantial for medical diagnosis and prediction. This approach can further be used with neurological tools. The initial status of the brain activities would act as a window into the brain; which can be used as an insight. With the influence of machine learning more generalized way of discriminating stress activities with other normal activities can be possible. © 2018 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2018
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Faraz, S. and Ali, S.S.A. and Adil, S.H.  (2018) Machine Learning and Stress Assessment: A Review.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063463913&doi=10.1109%2fICEEST.2018.8643313&partnerID=40&md5=13f210f328c47ecb580086e7d3a348da
relation: 10.1109/ICEEST.2018.8643313
identifier: 10.1109/ICEEST.2018.8643313