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Challenges and limitations of large language models in medical information extraction

Year: 2025

Type: conference-paper

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]

Source: German Medical Science (German Research Foundation)

DOI: 10.3205/25dkou468

Authors: Szép, Márton, Hinterwimmer, Florian, Breden, Sebastian, von Eisenhart-Rothe, Rüdiger, Rueckert, Daniel, Mogler, Carolin, Schüffler, Peter, Lazic, Igor, Seidl, Paulina

Institutions: TUM Klinikum, Technical University of Munich

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W7103193783

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