Medical Reasoning

Medical reasoning research focuses on developing computational models that mimic the complex decision-making processes of healthcare professionals, aiming to improve diagnostic accuracy and efficiency. Current efforts concentrate on adapting and evaluating large language models (LLMs), often augmented with knowledge graphs or retrieval mechanisms, across various clinical tasks and benchmarks, including question answering, diagnosis, and evidence summarization. This research is crucial for advancing the development of trustworthy and reliable AI systems in healthcare, potentially leading to improved patient care, more efficient workflows, and enhanced medical education.