Work

Large Language Model–Generated Expansion of the RadLex Ontology: Application to Multinational Datasets of Chest CT Reports

Year: 2026

Type: article

Abstract: The LLM-based approach provides a practical and scalable solution for expanding radiology ontologies while maintaining semantic alignment; the method can aid real-world natural language processing applications.

Source: American Journal of Roentgenology

DOI: 10.2214/ajr.25.34243

Authors: Taehee Lee, Hyungjin Kim, Seowoo Lee, Seonhye Chae, Charles E. Kahn, Seng Chan You, Edward Choi, Soon Ho Yoon

Institutions: Seoul National University, Seoul National University Hospital, University of Pennsylvania, Yonsei University, Yonsei University Health System, Korea Advanced Institute of Science and Technology, National Jewish Health

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: bronze

Funders: Kakao Brain, Daiichi Sankyo Europe

OpenAlex ID: W7124140448

FWCI: 1.939

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Cited by: 1

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