Artificial Intelligence Machine Learning And Mental Health In Pandemics
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Artificial Intelligence, Machine Learning, and Mental Health in Pandemics
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
Artificial Intelligence in Behavioral and Mental Health Care
Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings
Artificial Intelligence and Machine Learning in Healthcare
Author: Dharmendra Kumar Yadav
language: en
Publisher: Springer Nature
Release Date: 2023-10-29
This book is about the use of artificial intelligence (AI) and machine learning in healthcare. AI and related technologies are increasingly prevalent in business and society and are beginning to be applied to healthcare. These technologies have the potential to transform many aspects of patient care, as well as administrative processes within provider, payer, and pharmaceutical organizations. There are already a number of research studies suggesting that AI can perform as well as or better than humans at key healthcare tasks, such as diagnosing disease. Today, algorithms are already outperforming radiologists at spotting malignant tumors and guiding researchers in how to construct cohorts for costly clinical trials. However, for a variety of reasons, the authors believe that it will be many years before AI replaces humans for broad medical process domains. Through this book, the authors describe both the potential that AI offers to automate aspects of care and some of the barriers to rapid implementation of AI in healthcare.