Machine Learning Approaches to Identify and Predict the Presence and Severity of Suicidal Thoughts and Behaviors by Integrating Online Activity and Clinical Information

Suicide is one of the leading causes of death, yet suicide prevention remains difficult. Suicide risk is known to be associated with an individual’s social environment, as well as their affective and cognitive states. Given the continual adoption of online technologies, this research will integrate rich repositories of online and clinical data, via machine learning and natural language analysis, to identify novel predictors of suicidal thoughts and behaviors and to inform treatment and intervention research.