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 ...
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 ...
Abstract: Medical question answering aims to enhance diagnostic support, improve patient education, and assist in clinical decision-making by automatically answering medical-related queries, which is ...
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