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

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]

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Publication Details

Journal
German Medical Science (German Research Foundation)
Published
2025-11-03
DOI
https://doi.org/10.3205/25gmds061
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

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

German Medical Science (German Research Foundation)
Biomedical Text Mining and Ontologies
article

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

article en

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]

German Medical Science (German Research Foundation)
SLK-Kliniken Heilbronn (DE)
Quality Education
Openalex Percentile: Top 43%
Biomedical Text Mining and Ontologies
DOIOpen Access PDFOpenAlex
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Retrieval-Augmented Generation for Semantic Annotation of Clinical Trials on the Example of ICD-10 Codes · German Medical Science (German Research Foundation) (2025) | TGRS Research Map | TGRS