This research introduces LLM-MTD, a novel approach that leverages large language models to both detect depression in social media posts and generate medical explanations for the classifications.

• Performs dual-task processing: depression classification and medical explanation generation simultaneously
• Incorporates professional medical knowledge by aligning with established diagnostic criteria
• Offers explainable results that can help mental health professionals understand AI decisions
• Demonstrates how AI can support early intervention through social media screening

This advancement matters for healthcare by bridging the gap between AI capabilities and medical expertise, potentially enabling more accessible mental health screening while maintaining clinical relevance and transparency.

Generating Medically-Informed Explanations for Depression Detection using LLMs