We present MedNuggetizer, https://mednugget-ai.de/; access is available upon request.}, a tool for query-driven extraction and clustering of information nuggets from medical documents to support clinicians in exploring underlying medical evidence. Backed by a large language model (LLM), \textit{MedNuggetizer} performs repeated extractions of information nuggets that are then grouped to generate reliable evidence within and across multiple documents. We demonstrate its utility on the clinical use case of \textit{antibiotic prophylaxis before prostate biopsy} by using major urological guidelines and recent PubMed studies as sources of information. Evaluation by domain experts shows that \textit{MedNuggetizer} provides clinicians and researchers with an efficient way to explore long documents and easily extract reliable, query-focused medical evidence.

翻译：我们提出MedNuggetizer（访问链接：https://mednugget-ai.de/；需申请获取权限），这是一种基于查询驱动的医学文档信息块提取与聚类工具，旨在辅助临床医生探索潜在的医学证据。依托大型语言模型（LLM）的支持，MedNuggetizer通过重复提取信息块并进行分组，从而在单文档及多文档间生成可靠的证据。我们以《前列腺活检前抗生素预防》这一临床用例为例，通过整合主要泌尿科指南及近期PubMed研究文献作为信息源，展示了该工具的实际应用价值。领域专家评估表明，MedNuggetizer为临床医生和研究人员提供了一种高效探索长篇文档、便捷提取可靠且聚焦于查询需求的医学证据的方法。