Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide
Proceedings of a Workshop
Board on Health Care Services author National Academies of Sciences, Engineering, and Medicine author Health and Medicine Division author Forum on Mental Health and Substance Use Disorders author Robert Pool editor Sharyl J Nass editor Francis K Amankwah editor
Format:Paperback
Publisher:National Academies Press
Published:8th Jan '23
Currently unavailable, and unfortunately no date known when it will be back
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 <
ISBN: 9780309695060
Dimensions: unknown
Weight: unknown
96 pages