Development and internal validation of machine learning models for identifying suicidal behavior in inpatients with mood disorders

Background

Suicidal behavior (SB) is a major concern in mood disorders. Models developed from retrospective records are vulnerable to ambiguous targets, data leakage, and inappropriate handling of class imbalance. We developed and internally validated a model to identify the risk of suicidal behavior in patients with mood disorders upon admission.