Machine learning insight into the role of imaging and clinical variables for the prediction of obstructive coronary artery disease and revascularization: An exploratory analysis of the CONSERVE study-Reference-Cited by-同舟云学术

Machine learning insight into the role of imaging and clinical variables for the prediction of obstructive coronary artery disease and revascularization: An exploratory analysis of the CONSERVE study

Published:2020-06-25 Issue:6 Volume:15 Page:e0233791
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Baskaran Lohendran^ORCID,Ying Xiaohan^ORCID,Xu Zhuoran,Al’Aref Subhi J.,Lee Benjamin C.,Lee Sang-Eun,Danad Ibrahim,Park Hyung-Bok,Bathina Ravi,Baggiano Andrea,Beltrama Virginia,Cerci Rodrigo^ORCID,Choi Eui-Young,Choi Jung-Hyun,Choi So-Yeon,Cole Jason,Doh Joon-Hyung,Ha Sang-Jin,Her Ae-Young,Kepka Cezary,Kim Jang-Young,Kim Jin-Won,Kim Sang-Wook,Kim Woong,Lu Yao,Kumar Amit,Heo Ran,Lee Ji Hyun,Sung Ji-min,Valeti Uma,Andreini Daniele,Pontone Gianluca^ORCID,Han Donghee,Villines Todd C.,Lin Fay,Chang Hyuk-Jae,Min James K.,Shaw Leslee J.

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

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