Challenges and limitations of large language models in medical information extraction

Objectives: Large Language Models (LLMs) have demonstrated remarkable capabilities in general Natural Language Processing (NLP) tasks, sparking interest in their healthcare applications. However, their effectiveness in extracting complex, domain-specific medical information remains uncertain, despite [for full text, please go to the a.m. URL]

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Publication Details

Journal
German Medical Science (German Research Foundation)
Published
2025-10-31
DOI
https://doi.org/10.3205/25dkou468
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Challenges and limitations of large language models in medical information extraction

German Medical Science (German Research Foundation)
Artificial Intelligence in Healthcare and Education
article

Challenges and limitations of large language models in medical information extraction

article en

Abstract

Objectives: Large Language Models (LLMs) have demonstrated remarkable capabilities in general Natural Language Processing (NLP) tasks, sparking interest in their healthcare applications. However, their effectiveness in extracting complex, domain-specific medical information remains uncertain, despite [for full text, please go to the a.m. URL]

German Medical Science (German Research Foundation)
TUM Klinikum (DE)
Quality Education
Openalex Percentile: Top 50%
Artificial Intelligence in Healthcare and Education
DOIOpen Access PDFOpenAlex
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Challenges and limitations of large language models in medical information extraction · German Medical Science (German Research Foundation) (2025) | TGRS Research Map | TGRS