Artificial Intelligence, Machine Learning, and Mental Health in Pandemics
A Computational Approach

Explores how Artificial Intelligence (AI) and Machine Learning (ML) based solutions can assist with monitoring, detection, and intervention in mental health

Shikha Jain (Edited by), Kavita Pandey (Edited by), Princi Jain (Edited by), Kah Phooi Seng (Edited by)

9780323911962, Elsevier Science

Paperback / softback, published 22 April 2022

418 pages
22.9 x 15.2 x 2.6 cm, 0.68 kg

Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach provides a comprehensive guide for public health authorities, researchers and health professionals in psychological health. The book takes a unique approach by exploring how Artificial Intelligence (AI) and Machine Learning (ML) based solutions can assist with monitoring, detection and intervention for mental health at an early stage. Chapters include computational approaches, computational models, machine learning based anxiety and depression detection and artificial intelligence detection of mental health.

1. Mental Health impact of COVID-19 and Machine Learning Applications in Combating Mental Disorders: A Review
2. Multimodal Depression Detection using Machine Learning
3. A Graph Convolutional Networks based Framework for Mental Stress Prediction
4. Women Working in Healthcare Sector during COVID-19 in the National Capital Region of India: A Case Study
5. Impact of Covid19 on Women Educator
6. A Deep Learning approach towards Prediction of Mental Health of Indian’s Higher Education Students in Online mode of Teaching and Learning during Pandemic
7. Machine Learning based Analysis and Prediction of College Students’ Mental Health during COVID-19 in India.
8. Modeling the Impact of the COVID-19 Pandemic and Socio-economic Factors on Global Mobility and Its Effects on Mental Health
9. Depression Detection: Approaches, Challenges and Future Directions
10. Improving Mental Health Surveillance Over Twitter Text Classification Using Word Embedding Techniques
11. Predicting Loneliness from Social Media text using Machine Learning Techniques
12. Perceiving the Level of Depression from Web Text Using Deep Learning
13. Technologies for Vaccinating COVID-19, Its Variants and Future Pandemics: A Short Survey
14. A Blockchain Approach on Security of Health Records for Children Suffering from Dyslexia during Pandemic Covid -19.

Subject Areas: Educational psychology [JNC], Cognition & cognitive psychology [JMR], Physiological & neuro-psychology, biopsychology [JMM], Experimental psychology [JML], Child & developmental psychology [JMC], Psychology [JM], Cognitive science [GTR]