
Our approach achieved top performance across all three subtasks of the MEDIQA-CORR 2024 shared task, demonstrating the effectiveness of LLM-based programs in detecting, localizing, and correcting medical errors in clinical text.


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optimized-llm-based-programs-for-detecting-and-correcting-medical-errors-in-clinical-notes


Optimized LLM-based Programs for Detecting and Correcting Medical Errors in Clinical Notes


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This paper presents a multi-agent framework called MedReAct'N'MedReFlex that leverages large language models and retrieval-augmented generation to tackle the task of medical error detection and correction in clinical notes.


leveraging-medical-agents-and-retrieval-augmented-generation-to-tackle-medical-error-detection-and-correction


Leveraging Medical Agents and Retrieval-Augmented Generation to Tackle Medical Error Detection and Correction
