Under Review

In this paper, we introduce an AI-based automatic diagnosis framework, Agent-derived Multi-Specialist Consultation (AMSC), which mimics real-world medical consultations by using language models as virtual medical specialists. This approach outperforms previous methods by efficiently combining agents’ predictions on diseases, requiring less training and parameter updates.

In this paper, we introduce a method called knowledge-tuning, using structured medical knowledge bases to improve Large Language Models’ (LLMs) understanding and response accuracy in medical contexts, addressing the issue of hallucinated medical facts.