Interpretable Differential Diagnosis with Dual-Inference Large Language Models

Understand

Automatic differential diagnosis (DDx) is an essential medical task that generates a list of potential diseases as differentials based on patient symptom descriptions.

• In practice, interpreting these differential diagnoses yields significant value but remains under-explored.
• Given the powerful capabilities of large language models (LLMs), we investigated using LLMs for interpretable DDx.
• Specifically, we curated the first DDx dataset with expert-derived interpretation on 570 clinical notes.