How Machine Learning Can Help Prevent Suicide

Suicide is the 10th leading cause of death in the United States and the second leading cause of death among young people. Mental health professionals fare poorly at predicting suicide risk, mainly because patients hide these thoughts during counselling.

Machine learning and AI hold promise for analyzing patterns in data (EMR data and social media posts, for example) to help identify patients with suicidal thoughts and tendencies. These efforts toward an early warning system could help alert physicians, mental health professionals and family members when someone in their care needs help.

In this session, two healthcare experts discuss their efforts to use machine learning to detect suicidal thinking in two at-risk populations: convicts and veterans.

Key takeaways:

• The challenges of using behavioral prediction data
• How machine learning might help clinicians identify high-risk patients in clinical settings
• Speech analysis is a promising approach and can be useful in suicide ideation detection