MedNuggetizer: Confidence-Based Information Nugget Extraction from Medical Documents

This abstract has open access
Abstract Summary
We present \textbf{MedNuggetizer} (\url{https://mednugget-ai.de/}\footnote{\url{https://mednugget-ai.de/} \textit{username:} demo, \textit{password:} demo}), 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), 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.
Abstract ID :
NKDR163
Submission Type
Submission Topics

Associated Sessions

University Of Regensburg
PhD Student
,
University Of Regensburg
Professor
,
University Of Regensburg

Abstracts With Same Type

Abstract ID
Abstract Title
Abstract Topic
Submission Type
Primary Author
NKDR143
Applications Machine Learning and Large Language Models Recommender systems Search and ranking
Demos
Trung Vo
NKDR166
Applications Machine Learning and Large Language Models Search and ranking Societally-motivated IR research
Demos
Rodrigo Silva
NKDR168
Demos
Rishiraj Saha Roy
NKDR156
Applications Machine Learning and Large Language Models Search and ranking System aspects
Demos
Quang Hieu Vu
NKDR159
Applications Machine Learning and Large Language Models Search and ranking
Demos
Rodrigo Duarte
NKDR160
Applications Conversational search and recommender systems Societally-motivated IR research
Demos
Markos Dimitsas
NKDR27
Evaluation researchMachine Learning and Large Language ModelsRecommender systems
Demos
Lukas Wegmeth
1 visits