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.
@article{arxiv.2512.15384,
title = {MedNuggetizer: Confidence-Based Information Nugget Extraction from Medical Documents},
author = {Gregor Donabauer and Samy Ateia and Udo Kruschwitz and Maximilian Burger and Matthias May and Christian Gilfrich and Maximilian Haas and Julio Ruben Rodas Garzaro and Christoph Eckl},
journal= {arXiv preprint arXiv:2512.15384},
year = {2025}
}