AINeutralarXiv – CS AI · 18h ago6/10
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RadOT-Eval: Auditable Structured-Evidence Transport for Radiology Report Evaluation
RadOT-Eval is a new AI framework that uses optimal transport algorithms to automatically evaluate radiology report generation by decomposing reports into structured clinical evidence units and detecting specific error types like omissions, hallucinations, and polarity reversals. The method achieves higher correlation with clinician-annotated errors than existing metrics and LLM-based evaluators, providing an auditable approach for quality assurance in high-stakes medical AI applications.