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

  • Shikha Jain
  • , Kavita Pandey
  • , Princi Jain
  • , Kah Phooi Seng
    • Jaypee University of Information Technology, Solan
    • Atal Bihari Vajpayee Institute of Medical Sciences
    • Dr. Ram Manohar Lohia Hospital
    • Queensland University of Technology

    Research output: Book/Report/Edited volume › Book › peer-review

    9 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    PublisherElsevier
    Number of pages374
    ISBN (Electronic)9780323911962
    ISBN (Print)9780323915557
    DOIs
    Publication statusPublished - 1 Jan 2022

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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