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

Posters

Keyword: Suicide

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.

• Chloe Lau (Presenting Author)
• Anthony Ruocco (Author)
• Darren Courtney (Author)
• Kristin Cleverley (Author)
• George Foussias (Author)
• Stephanie Ameis (Author)
• Erin Dickie (Author)
• Daniel Felsky (Author)
• Benjamin Goldstein (Author)
• Lisa Hawke (Author)
• Nicole Kozloff (Author)
• Yuliya Nikolova (Author)
• Alexia Polillo (Author)
• Martin Rotenberg (Author)
• Wanda Tempelaar (Author)
• Wei Wang (Author)
• Jimmy Wong (Author)
• Aristotle Voineskos (Author)
• Lena Quilty (Author)