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Can I read Artificial Intelligence, Machine Learning, and Mental Health in Pandemics : A Computational Approach on EtoBox?

Artificial Intelligence, Machine Learning, and Mental Health in Pandemics : A Computational Approach by Shikha Jain, Kavita Pandey, Princi Jain, Kah Phooi Seng is a nonfiction available to read on EtoBox.

What is Artificial Intelligence, Machine Learning, and Mental Health in Pandemics : A Computational Approach about?

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. Examines the datasets and algorithms that can be used to detect mental disorders Covers machine learning solutions that can help determine the precautionary measures of psychological health problems Highlights innovative AI solutions and bi-statistics computation that can strengthen day-to-day medical procedures and decision-making

Who reads Artificial Intelligence, Machine Learning, and Mental Health in Pandemics : A Computational Approach?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Shikha Jain, Kavita Pandey, Princi Jain, Kah Phooi Seng
Publisher
ELSEVIER ACADEMIC PRESS
Published
2022
Language
EN
ISBN
9780323911962
Category
nonfiction
Subjects
Medical, Psychology, Computer Science

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