Diagnosis Task

Disease diagnosis is increasingly leveraging artificial intelligence, particularly large language models (LLMs), to analyze diverse clinical data including text and images, aiming to improve diagnostic accuracy and efficiency. Current research focuses on developing LLMs capable of multi-step diagnostic reasoning, incorporating external planning modules for proactive data gathering, and providing interpretable guidance to human clinicians rather than fully automated decisions. These advancements hold significant potential for improving healthcare by assisting clinicians in complex diagnostic tasks and potentially reducing diagnostic errors, although careful evaluation and consideration of human-AI interaction are crucial.