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TabMedQA: From Structured Data to Question-Answer Datasets in Early Clinical Decision-Making

2026-08-21

Abstract excerpt

The rising adoption of Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) in clinical general practice demands datasets that capture realistic early-stage clinical decision-making, where experts must decide on follow-up actions based on sparse, structured patient data. Existing medical Question-Answering (QA) resources primarily address post-diagnostic or specialist settings and rarely reflect h...

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Literature Corpus work: b358e734-db0e-5b65-9dd5-1f6b343afd53
DOI: 10.64898/2026.08.19.26360779

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