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Peer-Reviewed Publication
Radiol Artif Intell2025;7(3):e240459.May 1, 2025Journal Article

Predicting Major Adverse Cardiac Events Using Deep Learning-based Coronary Artery Disease Analysis at CT Angiography.

Jin Young Kim1, Kye Ho Lee2, Ji Won Lee3, Jiyong Park4, Jinho Park4, Pan Ki Kim4, Kyunghwa Han5, Song-Ee Baek5, Dong Jin Im5, Byoung Wook Choi5, Jin Hur5
1Department of Radiology, Keimyung University Dongsan Hospital, Keimyung University School of Medicine, Daegu, Republic of Korea.
2Department of Radiology, Dankook University Hospital, Cheonan, Republic of Korea.
3Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea.
4Department of Research and Development, Phantomics, Seoul, Republic of Korea.
5Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
PubMed DOI

Abstract

Purpose To evaluate the predictive value of deep learning (DL)-based coronary artery disease (CAD) extent analysis for major adverse cardiac events (MACEs) in patients with acute chest pain presenting to the emergency department (ED). Materials and Methods This retrospective multicenter observational study included consecutive patients with acute chest pain who underwent coronary CT angiography (C…

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