RadCoT: a Radiological Chain-of-Thought framework for enhanced error detection in radiology reports
Errors in radiology reports are a major patient-safety concern and are difficult to detect with manual quality assurance (QA). Large language models (LLMs) can assist, but generic prompting does not reflect radiologists’ structured, section-based workflows. To develop and evaluate RadCoT (Radiological Chain-of-Thought)...