Interpretable depressive symptoms screening via statistical reasoning-augmented large language models using wearable and environmental data (opens in new tab)

Early assessment of depressive symptoms is essential for scalable and personalized mental health care. We developed a hybrid clinical decision support system (CDSS) that combines interpretable logistic regression with fine-tuned large language models (LLMs) to classify depressive symptom status using wearable-derived behavior, clinical features, and environmental exposures. This study aimed to develop a hybrid clinical decision support system by fine‑tuning a GPT‑based large language model wi...