Electronic Medical Record–Based Machine Learning Approach to Predict the Risk of 30-Day Adverse Cardiac Events After Invasive Coronary Treatment: Machine Learning Model Development and Validation

Osung Kwon   ^{1 *} , MD, PhD ;   Wonjun Na   ^{2 *} , MS ;   Heejun Kang   ³ , MS ;   Tae Joon Jun   ³ , PhD ;   Jihoon Kweon   ³ , PhD ;   Gyung-Min Park   ⁴ , MD, PhD ;   YongHyun Cho   ⁵ , MS ;   Cinyoung Hur   ⁵ , MS ;   Jungwoo Chae   ⁵ , BS ;   Do-Yoon Kang   ³ , MD, PhD ;   Pil Hyung Lee   ³ , MD, PhD ;   Jung-Min Ahn   ³ , MD, PhD ;   Duk-Woo Park   ³ , MD, PhD ;   Soo-Jin Kang   ³ , MD, PhD ;   Seung-Whan Lee   ³ , MD, PhD ;   Cheol Whan Lee   ³ , MD, PhD ;   Seong-Wook Park   ³ , MD, PhD ;   Seung-Jung Park   ³ , MD, PhD ;   Dong Hyun Yang   ^{6 *} , MD, PhD ;   Young-Hak Kim   ^{3 *} , MD, PhD

¹ Division of Cardiology Department of Internal Medicine, Eunpyeong St Mary's Hospital, Catholic University of Korea, Seoul, Republic of Korea

² Department of Medical Science, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea

³ Division of Cardiology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea

⁴ Division of Cardiology, Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea

⁵ Artificial Intelligence Lab, Linewalks, Inc, Seoul, Republic of Korea

⁶ Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea

*these authors contributed equally