Linking Uncertainty in Physicians' Narratives to Diagnostic Correctness

Towards multimodal modeling of physicians' diagnostic confidence and self-awareness using medical narratives

Human-LLM Dialogue Improves Diagnostic Accuracy in Emergency Care

Clinical decision-making in emergency medicine demands rapid, accurate diagnoses under uncertainty. Despite benchmark progress, evidence for LLMs as interactive aids in live physician workflows remains sparse. MedSyn let…

Uncertainty-Aware Learning Policy for Reliable Pulmonary Nodule Detection on Chest X-Ray

Early detection and rapid intervention of lung cancer are crucial. Nonetheless, ensuring an accurate diagnosis is challenging, as physicians' ability to interpret chest X-rays varies significantly depending on their expe…

Reverse Physician-AI Relationship: Full-process Clinical Diagnosis Driven by a Large Language Model

Full-process clinical diagnosis in the real world encompasses the entire diagnostic workflow that begins with only an ambiguous chief complaint. While artificial intelligence (AI), particularly large language models (LLM…

A Specialized Large Language Model for Clinical Reasoning and Diagnosis in Rare Diseases

Rare diseases affect hundreds of millions worldwide, yet diagnosis often spans years. Convectional pipelines decouple noisy evidence extraction from downstream inferential diagnosis, and general/medical large language mo…