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...

Полное описание

Сохранить в:
Библиографические подробности
Опубликовано в: :J Am Heart Assoc
Главные авторы: 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
Формат: Artigo
Язык:Inglês
Опубликовано: John Wiley and Sons Inc. 2020
Предметы:
Original Research
Online-ссылка: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
Метки: Добавить метку
Нет меток, Требуется 1-ая метка записи!

Схожие документы