Interpretable machine learning for depression symptom classification in NHANES: Performance in a curated high-confidence corpus and the full survey population.

Depressive disorders are among the most common psychiatric conditions worldwide and frequently remain undetected or misinterpreted. Scalable computational tools may help characterize depressive-symptom patterns in large health datasets, but their clinical use requires realistic validation and calibr