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Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide - Proceedings of a Workshop (Paperback)
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Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide - Proceedings of a Workshop (Paperback)
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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 Contents Front Matter Workshop Overview
Appendix A: Statement of Task Appendix B: Workshop Agenda
General
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