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Retrieval-Augmented Generation for Semantic Annotation of Clinical Trials on the Example of ICD-10 Codes

Year: 2025

Type: conference-paper

Abstract: Introduction: Accurate, structured annotation of clinical research data is essential to support personalized oncology workflows, such as matching patients to relevant clinical trials [ref:1]. However, manual coding of clinical diagnoses using standardized terminologies remains time-consuming [for full text, please go to the a.m. URL]

Source: German Medical Science (German Research Foundation)

DOI: 10.3205/25gmds061

Authors: Lehmann, Paula, Mathes, Georg, Vishnevskaya, Valeriya, Bochum, Sylvia, Sigle, Stefan

Institutions: MOLIT Institut für Personalisierte Medizin, SLK-Kliniken Heilbronn

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7103884603

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