Open AccessCT Angiographic and Plaque Predictors of Functionally Significant Coronary Disease and Outcome Using Machine Learning
Author(s) -
Seokhun Yang,
BonKwon Koo,
Masahiro Hoshino,
Joo Myung Lee,
Tadashi Murai,
Jiesuck Park,
Jinlong Zhang,
Doyeon Hwang,
EunSeok Shin,
JoonHyung Doh,
ChangWook Nam,
Jianan Wang,
ShaoLiang Chen,
Nobuhiro Tanaka,
Hitoshi Matsuo,
Takashi Akasaka,
Gilwoo Choi,
Kersten Petersen,
HyukJae Chang,
Tsunekazu Kakuta,
Jagat Narula
Publication year - 2020
Publication title -
jacc. cardiovascular imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.79
H-Index - 120
eISSN - 1936-878X
pISSN - 1876-7591
DOI - 10.1016/j.jcmg.2020.08.025
Subject(s) - outcome (game theory) , medicine , coronary angiography , cardiology , coronary artery disease , radiology , myocardial infarction , mathematics , mathematical economics
The goal of this study was to investigate the association of stenosis and plaque features with myocardial ischemia and their prognostic implications.
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