The Medical RAG System is designed to enhance medical information retrieval and provide accurate answers to medical queries. It combines various retrieval methods, including BM25, bioBERT, and hybrid ...
Abstract: Advances in large language models have driven progress in medical question-answering systems, but challenges remain in accuracy and relevance, especially in complex medical settings. To ...
Abstract: Research in medical visual question answering (MVQA) can contribute to the development of computer-aided diagnosis. MVQA is a task that aims to predict accurate and convincing answers based ...
Evaluating natural language generation (NLG) systems in the medical domain presents unique challenges due to the critical demands for accuracy, relevance, and domain-specific expertise. Traditional ...
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