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.