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Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide : Proceedings of a Workshop

By: (Author) Board on Health Care Services , (Author) and Medicine National Academies of Sciences Engineering , (Author) Forum on Mental Health and Substance Use Disorders , (Author) Health and Medicine Division , (Edited by) Francis K. Amankwah , (Edited by) Ph.D. Pool Robert , (Edited by) Sharyl J. Nass

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Ksh 3,950.00

Format: Paperback or Softback

ISBN-10: 0309695066

ISBN-13: 9780309695060

Publisher: National Academies Press

Imprint: National Academies Press

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Jan 8th, 2023

Print length: 96 Pages

Product Classification: Medicine
Public health & preventive medicine
Neurology & clinical neurophysiology

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Emerging real-time data sources, together with innovative data science techniques and methods - including artificial intelligence and machine learning - can help inform upstream suicide prevention efforts. Select social media platforms have proactively deployed these methods to identify individual platform users at high risk for suicide, and in some cases may activate local law enforcement, if needed, to prevent imminent suicide. To explore the current scope of activities, benefits, and risks of leveraging innovative data science techniques to help inform upstream suicide prevention at the individual and population level, the Forum on Mental Health and Substance Use Disorders of the National Academies of Sciences, Engineering, and Medicine convened a virtual workshop series consisting of three webinars held on April 28, May 12, and June 30, 2022. This Proceedings highlights presentations and discussions from the workshop. Table of ContentsFront MatterWorkshop OverviewAppendix A: Statement of TaskAppendix B: Workshop Agenda

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Mind, Body, & Spirit