{"ID":2828023,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.15384","arxiv_id":"2512.15384","title":"MedNuggetizer: Confidence-Based Information Nugget Extraction from Medical Documents","abstract":"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.","short_abstract":"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...","url_abs":"https://arxiv.org/abs/2512.15384","url_pdf":"https://arxiv.org/pdf/2512.15384v1","authors":"[\"Gregor Donabauer\",\"Samy Ateia\",\"Udo Kruschwitz\",\"Maximilian Burger\",\"Matthias May\",\"Christian Gilfrich\",\"Maximilian Haas\",\"Julio Ruben Rodas Garzaro\",\"Christoph Eckl\"]","published":"2025-12-17T12:37:44Z","proceeding":"cs.IR","tasks":"[\"cs.IR\"]","methods":"[\"Large Language Model\",\"Language Model\"]","project_urls":"[\"https://mednugget-ai.de/\"]","has_code":false}