Predicting Suicide Attempts in Youth: A Machine Learning Model Proposal Integrating Clinical and Cognitive Risk Factors

Virtual · October 2025

Poster · Clinical Science

Chloe Lau
Centre for Addiction and Mental Health
Anthony Ruocco
Darren Courtney
Kristin Cleverley
George Foussias
Stephanie Ameis
Erin Dickie
Daniel Felsky
Benjamin Goldstein
Lisa Hawke
Nicole Kozloff
Yuliya Nikolova
Alexia Polillo
Martin Rotenberg
Wanda Tempelaar
Wei Wang
Jimmy Wong
Aristotle Voineskos
Lena Quilty
Centre for Addiction and Mental Health

Abstract

This study develops a predictive model of youth suicide attempts using clinical and cognitive data, analyzed with machine learning. Drawing on CAMH’s TAY Cohort, it evaluates cognitive control deficits and gender identity interactions. Results will inform suicide risk assessment and prevention strategies in youth mental health services.

Suicide

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Predicting Suicide Attempts in Youth: A Machine Learning Model Proposal Integrating Clinical and Cognitive Risk Factors

Abstract

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