An LLM-Driven Multi-Agent Debate System for Mendelian Diseases

Understand

Accurate diagnosis of Mendelian diseases is crucial for precision therapy and assistance in preimplantation genetic diagnosis.

• However, existing methods often fall short of clinical standards or depend on extensive datasets to build pretrained machine learning models.
• To address this, we introduce an innovative LLM-Driven multi-agent debate system (MD2GPS) with natural language explanations of the diagnostic results.
• It utilizes a language model to transform results from data-driven and knowledge-driven agents into natural language, then fostering a debate between these two specialized agents.