Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop
English
By (author): and Medicine Board on Health Care Services Engineering Forum on Mental Health and Substance Use Disorders Health and Medicine Division National Academies of Sciences
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