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

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


PRODUCT DETAILS

ISBN-13: 9780309695060
Publisher: National Academies Press
Publication date: January, 2023
Pages: 78
Weight: 652g
Availability: Available
Subcategories: Neurology, Public Health

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