MIMIC-IV-Ext-DiReCT

Large language models (LLMs) have recently demonstrated remarkable
capabilities across a broad spectrum of tasks and applications, including the
medical field. Models like GPT-4 excel in medical question answering but
encounter challenges in interpretability when managing complex tasks in real
clinical settings. To address this, we introduce the Diagnostic Reasoning
Dataset for Clinical Notes (DiReCT), designed to evaluate the reasoning
ability and interpretability of LLMs compared to human doctors. The dataset
comprises 511 clinical notes (sourced from MIMIC-IV), each meticulously
annotated by physicians, detailing the diagnostic reasoning process from
initial observations to the final diagnosis.