Project

This research aims to develop machine learning models to improve understanding of suicide-related outcomes across different stages of adolescence. The first study conducted a meta-analysis of the performance of machine learning models used to predict suicide-related outcomes in the population. It aggregated the performance using best-practice analyses, and identifies strengths, limitations, and gaps in current research. The subsequent studies have used machine learning models to examine suicide outcomes including self harm, ideation and attempts at two stages of adolescences in an Australian cohort.