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
The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena.
This edited book defines the state of scientific research related to the development, experimental evaluation, and effective dissemination of technology-based therapeutic tools targeting behavioral health.Behavioral Healthcare and ...
The book examines the role of artificial intelligence during the COVID-19 pandemic, including its application in i) early warnings and alerts, ii) tracking and prediction, iii) data dashboards, iv) diagnosis and prognosis, v) treatments, ...
This book reviews key recent advances and new frontiers within psychiatric research and clinical practice.
This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations.
With this book, business stakeholders and practitioners will be able to build knowledge, a roadmap, and the confidence to support AIin their organizations—without getting into the weeds of algorithms or open source frameworks.
Intriguingly, recent studies have found that GWAS results for psychiatric illnesses connect to brain cell types (i.e., ... toward greater data sharing and collaboration has been climactic to scientific discovery in psychiatric genetics.
This book is a blueprint for how this could and should occur in mental health in order to solve the complex, multi-system problems that the field faces.
However, using these tools in practice raises many practical and ethical questions. The book explains current technological developments in therapy, including mobile apps, telemental health, and virtual reality programs.
Daniel Barron, a psychiatrist who trained at the Yale School of Medicine, asks a provocative and important question: Is psychiatry scientific enough?