This paper is in the following e-collection/theme issue:

Methods and Instruments in Medical Informatics (211) Medical imaging (129) Coronary Heart Disease (113) Advanced Data Analytics in eHealth (232) Imaging Informatics (325) Ontologies, Classifications, and Coding (346) mHealth for Data Collection and Research (1245) Artificial Intelligence (2314) Clinical Information and Decision Making (2048)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70967, first published .
Leveraging GPT-4o for Automated Extraction and Categorization of CAD-RADS Features From Free-Text Coronary CT Angiography Reports: Diagnostic Study

Leveraging GPT-4o for Automated Extraction and Categorization of CAD-RADS Features From Free-Text Coronary CT Angiography Reports: Diagnostic Study

Leveraging GPT-4o for Automated Extraction and Categorization of CAD-RADS Features From Free-Text Coronary CT Angiography Reports: Diagnostic Study

Authors of this article:

Youmei Chen1 Author Orcid Image ;   Mengshi Dong1 Author Orcid Image ;   Jie Sun1 Author Orcid Image ;   Zhanao Meng1 Author Orcid Image ;   Yiqing Yang1 Author Orcid Image ;   Abudushalamu Muhetaier1 Author Orcid Image ;   Chao Li1 Author Orcid Image ;   Jie Qin1 Author Orcid Image
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Journals

  1. Kaba E, Çubukçu Y, Uzunibrahimoğlu B, Yılmaz Y, Çınar M, Tabakoğlu S, Bal E, Beydüz Y, Solak M, Oğuz E, Varlık A, Malkoç G, Beyazal M, Celiker F, Akkaya S. Retrieval-augmented generation-enhanced large language models for comprehensive CAD-RADS 2.0 categorization from structured coronary CTA reports. Die Radiologie 2026 View