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...

Πλήρης περιγραφή

Αποθηκεύτηκε σε:
Λεπτομέρειες βιβλιογραφικής εγγραφής
Τόπος έκδοσης:J Am Heart Assoc
Κύριοι συγγραφείς: 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
Μορφή: Artigo
Γλώσσα:Inglês
Έκδοση: John Wiley and Sons Inc. 2020
Θέματα:
Original Research
Διαθέσιμο Online: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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