Assessing the Limitations of Large Language Models in Clinical Practice Guideline–Concordant Treatment Decision-Making on Real-World Data: Retrospective Study

Even advanced LLMs require extensively curated input for informed treatment decisions. Unreliable responses, bias, and hallucinations pose significant health risks and highlight the need for caution in applying LLMs to real-world clinical decision-making.

Authors

Institutions

Publication Details

Journal
JMIRx Med
Published
2025-11-03
DOI
https://doi.org/10.2196/74899
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the Limitations of Large Language Models in Clinical Practice Guideline–Concordant Treatment Decision-Making on Real-World Data: Retrospective Study

Tobias Daniel Trippel, Tobias Roeschl, Marie Hoffmann, Jörg Kempfert et al.
1 citations
JMIRx Med
Artificial Intelligence in Healthcare and Education
0.65
article

Assessing the Limitations of Large Language Models in Clinical Practice Guideline–Concordant Treatment Decision-Making on Real-World Data: Retrospective Study

Tobias Daniel Trippel, Tobias Roeschl, Marie Hoffmann, Jörg Kempfert, Matthias I. Gröschel, Volkmar Falk, Gerhard Hindricks, Henryk Dreger, Axel Unbehaun, Benjamin O’Brien, Felix Balzer, Nils Hinrichs, Djawid Hashemi, Alexander Meyer, Christoph Klein, Felix Rarreck
article en
1 citations

Abstract

Even advanced LLMs require extensively curated input for informed treatment decisions. Unreliable responses, bias, and hallucinations pose significant health risks and highlight the need for caution in applying LLMs to real-world clinical decision-making.

JMIRx MedVol. 6
St Bartholomew's Hospital (GB), Humboldt-Universität zu Berlin (DE), Deutsches Herzzentrum der Charité (DE), German Centre for Cardiovascular Research (DE), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), Technische Universität Berlin (DE), École Polytechnique Fédérale de Lausanne (CH), Freie Universität Berlin (DE), Charité - Universitätsmedizin Berlin (DE)
Openalex Percentile: Top 20%
Artificial Intelligence in Healthcare and Education
0.65
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.