Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: from the PARADIGM Registry
Donghee Han,Kranthi K. Kolli,Subhi J. Al'Aref,Lohendran Baskaran,Alexander R. van Rosendael,Heidi Gransar,Daniele Andreini,Matthew J. Budoff,Filippo Cademartiri,Kavitha Chinnaiyan,Jung Hyun Choi,Edoardo Conte,Hugo Marques,Pedro de Araujo Goncalves,Ilan Gottlieb,Martin Hadamitzky,Jonathon A. Leipsic,Erica Maffei,Gianluca Pontone,Gilbert L. Raff,Sangshoon Shin,Yong-Jin Kim,Byoung Kwon Lee,Eun Ju Chun,Ji Min Sung,Sang-Eun Lee,Renu Virmani,Habib Samady,Peter Stone,Jagat Narula,Daniel S. Berman,Jeroen J. Bax,Leslee J. Shaw,Fay Y. Lin,James K. Min,Hyuk-Jae Chang Journal of the American Heart Association（2020）
Key words
coronary artery disease,coronary computed tomography angiography,machine learning,plaque progression,risk prediction
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