Related Experiment Video
Updated: Dec 6, 2025
07:31
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
7.4K
AI enabled suicide prediction tools: a qualitative narrative review
Daniel D'Hotman1, Erwin Loh2,3
1Oxford Uehiro Centre for Practical Ethics, University of Oxford, Oxford, United Kingdom daniel.dhotman@philosophy.ox.ac.uk.
BMJ Health & Care Informatics
|October 10, 2020
Summary
Artificial intelligence (AI) offers new tools for suicide prediction. AI-driven medical and social suicide prediction shows promise in identifying at-risk individuals, potentially saving lives.
Area of Science:
- Digital Health
- Public Health
- Artificial Intelligence
Background:
- Suicide is a major global health concern.
- Barriers to care include stigma, forced treatment fears, and poor insight into mental state.
- Healthcare providers face challenges in identifying individuals at risk of suicide.
Purpose of the Study:
- To review research on AI-driven suicide prediction tools.
- To explore medical and social suicide prediction approaches.
- To assess the potential of AI in mitigating suicide risk.
Main Methods:
- A qualitative narrative review of research.
- Searches conducted on Google Scholar and PubMed from 2017 onwards.
- Focus on artificial intelligence applications in suicide prediction.
Main Results:
- AI-driven suicide prediction tools show promising initial evidence.
- Medical suicide prediction may be ethically sound if respecting principles.
- Social suicide prediction offers a novel approach for those not using traditional services.
Conclusions:
- AI has the potential to enhance suicide risk identification and save lives.
- Further research is needed to validate medical suicide prediction tools across contexts.
- Social suicide prediction requires independent oversight for safety, effectiveness, and ethics.
