August 2024
Intermediate to advanced
256 pages
8h 8m
English
Content preview from Smart Sensors for Industry 4.0
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9Text-Based Prediction and Classification Model of Stress, Anxiety and Depression Among Indians
KKishor Kumar Reddy C1, Tungana Bhavya1, Anisha P R1, Marlia Mohd Hanafiah2,3
1 Department of Computer Science & Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, Telangana, India
2 Department of Earth Science and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, Selangor, Malaysia
3 Centre for Tropical Climate Change System, Institute of Climate Change, Universiti Kebangsaan Malaysia (UKM), Bangi, Selangor, Malaysia
Email: tbhavya054@gmail.com
Abstract
In today’s contemporary life, the occurrence of stress, anxiety and depression is becoming common in everyone due to social demographic, behavioral and educational factors and has a serious impact on the individual’s life and the society which can lead to negative outcomes such as suicidal thoughts and suicide attempts. The current research applied various deep learning techniques on the data and developed and compared a model for an effective prediction of stress, anxiety and depression levels among people based on different criteria. Furthermore, the proposed work focuses on identifying the various levels of stress, anxiety and depression among people using logistic regression, decision trees and Näıve Bayes algorithms to classify different classes of stress, anxiety and depression based on different criteria such as age, gender, profession, marital status, ...
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