Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry

BACKGROUND: Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography–determined qualitative and q...

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Detalhes bibliográficos
Publicado no:J Am Heart Assoc
Main Authors: Han, Donghee, Kolli, Kranthi K., Al'Aref, Subhi J., Baskaran, Lohendran, van Rosendael, Alexander R., Gransar, Heidi, Andreini, Daniele, Budoff, Matthew J., Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Conte, Edoardo, Marques, Hugo, de Araújo Gonçalves, Pedro, Gottlieb, Ilan, Hadamitzky, Martin, Leipsic, Jonathon A., Maffei, Erica, Pontone, Gianluca, Raff, Gilbert L., Shin, Sangshoon, Kim, Yong‐Jin, Lee, Byoung Kwon, Chun, Eun Ju, Sung, Ji Min, Lee, Sang‐Eun, Virmani, Renu, Samady, Habib, Stone, Peter, Narula, Jagat, Berman, Daniel S., Bax, Jeroen J., Shaw, Leslee J., Lin, Fay Y., Min, James K., Chang, Hyuk‐Jae
Formato: Artigo
Idioma:Inglês
Publicado em: John Wiley and Sons Inc. 2020
Assuntos:
Original Research
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7335586/
https://ncbi.nlm.nih.gov/pubmed/32089046
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1161/JAHA.119.013958
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