Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide

National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Care Services, Forum on Mental Health and Substance Use Disorders

Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide
Format
Paperback
Publisher
National Academies Press
Country
United States
Published
8 January 2023
Pages
96
ISBN
9780309695060

Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide

National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Care Services, Forum on Mental Health and Substance Use Disorders

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 Contents

Front Matter Workshop Overview Appendix A: Statement of Task Appendix B: Workshop Agenda

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