A Clinical Risk Prediction Model for Depressive Disorders Based on Seven Machine Learning Algorithms

This study successfully developed a clinically interpretable risk prediction model for depressive disorders by integrating machine learning algorithms and routine blood test indicators. The logistic regression model demonstrated robust performance across all metrics and holds potential as a reliable auxiliary tool for the diagnosis of depressive disorders.