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

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. With the increase in number of natural disasters and the ongoing pandemic, people are experiencing uncertainty, leading to fear, anxiety and depression, hence this is a timely resource on the latest updates in the field. Review Explores how Artificial Intelligence (AI) and Machine Learning (ML) based solutions can assist with monitoring, detection, and intervention in mental health From the Back Cover With the increase in number of natural disasters and the ongoing pandemic, people are experiencing uncertainty, leading to fear, anxiety and depression. <i>Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach </i>provides a comprehensive guide for public health authorities, researchers and health professionals in psychological health. This 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 model, machine Learning based anxiety and depression detection and Artificial intelligence detection of mental health. About the Author Shikha Jain is presently working with Jaypee Institute of Information Technology (JIIT), NOIDA, INDIA as Assistant Professor. She has more than seventeen years of research and academic experience. She has received her PhD in computer science from Jaypee Institute of Information Technology, Noida, India. She has published a number of research papers in the renowned journals and conferences. She was advisory board member of a book entitled “Nature-Inspired Algorithms for Big Data Frameworks, IGI Global. She was a guest editor of a special issue “Advances in Computational Intelligence and its applications in International Journal of Information Retrieval Research (Publishing phase). She is active reviewer of many International Journals and technical program committee member of various International Conferences. Her research area includes Affective Computing, Emotion Modelling, Cognitive Affective Architectures, Machine Learning and Soft Computing. She is a senior member of IEEE. Kavita Pandey received her B.Tech. in Computer Science and Engineering from M.D. University in 2002 and M.Tech. (CS) from Banasthali Vidyapeeth University in year 2003. She has obtained her Ph.D. (CS) from Jaypee Institute of Information Technology (JIIT), Noida, India in January, 2017. She is currently working as an Assistant Professor (Senior Grade) in JIIT, Noida. Her research interests include Soft Computing, Machine Learning, Vehicular Ad hoc Networks, Internet of Things and Optimization Techniques. She has published various papers in International journals and conferences including Wiley, IEEE, Springer, Inderscience, etc. She worked as a guest editor of special issue, "Advances in Computational Intelligence and Applications" in International Journal of Information Retrieval Research (IJIRR), IGI Global, ESCI, Web of Science. She worked as a reviewer in many international journals of renowned publishers including Elsevier, Inderscience, IEEE Access, etc. She is an active TPC member of many conferences such as REDSET, IC3, UPCON, TEAMC, ICTCS and many more. She is also a senior member of IEEE society. Dr. Prin