BLUEmed: Retrieval-Augmented Multi-Agent Debate for Clinical Error Detection
Terminology substitution errors in clinical notes, where one medical term is replaced by a linguistically valid but clinically different term, pose a persistent challenge for automated error detection in healthcare. We introduce BLUEmed, a multi-agent debate framework augmented with hybrid Retrieval-Augmented Generation (RAG) that combines evidence-grounded reasoning with multi-perspective verification for clinical error detection. BLUEmed decomposes each clinical note into focused sub-queries, retrieves source-partitioned evidence through dense, sparse, and online retrieval, and assigns two domain expert agents distinct knowledge bases to produce independent analyses; when the experts di...
| Authors | Saukun Thika You, Nguyen Anh Khoa Tran, Wesley K. Marizane et al. |
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| Primary category | cs.CL |
| Published | 12 April 2026 |
| Last updated at source | 11 June 2026 |
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