Machine Learning and Stress Assessment: A Review

Faraz, S. and Ali, S.S.A. and Adil, S.H. (2018) Machine Learning and Stress Assessment: A Review. In: UNSPECIFIED.

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Abstract

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.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 5; Conference of 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018 ; Conference Date: 21 December 2018 Through 22 December 2018; Conference Code:145373
Uncontrolled Keywords: Brain; Computer aided diagnosis; Computer aided instruction; Neurology; Risk assessment, Brain activity; Heart attack; Learning assessment; Machine-learning; Medical experts; Stress assessment, Machine learning
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:36
Last Modified: 09 Nov 2023 16:36
URI: https://khub.utp.edu.my/scholars/id/eprint/10145

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