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Using Supervised Machine Learning to Predict the Role of Cognitive Control in the Suicide Ideation-to-Action Model

2023 Postdoctoral Fellowship

Amount Awarded: $140,000

Focus Area: Psychosocial

Chloe Lau, Ph.D.

Chloe Lau, Ph.D.

Centre for Addiction and Mental Health (Canada)

Inside the Research

The proposed study aims to predict suicide attempts with supervised machine learning algorithms (artificial intelliigence) using clinical and cognitive information such as symptoms and memory functions. This project uses the CAMH Toronto Adolescent and Youth Cohort Study recruiting youth (ages 11 to 24) over five years. A large-scale longitudinal study of service-seeking youth would be ideally positioned to identify a variety of risk factors that work together to predict suicide attempts in youth, and identify youth at increased risk for suicide.