Angiography‐Based Machine Learning for Predicting Fractional Flow Reserve in Intermediate Coronary Artery Lesions-Reference-Cited by-同舟云学术

Angiography‐Based Machine Learning for Predicting Fractional Flow Reserve in Intermediate Coronary Artery Lesions

Published:2019-02-19 Issue:4 Volume:8 Page:
ISSN:2047-9980
Container-title:Journal of the American Heart Association
language:en
Short-container-title:JAHA

Author:

Cho Hyungjoo¹,Lee June‐Goo²,Kang Soo‐Jin¹,Kim Won‐Jang³,Choi So‐Yeon⁴,Ko Jiyuon²,Min Hyun‐Seok¹,Choi Gun‐Ho¹,Kang Do‐Yoon¹,Lee Pil Hyung¹,Ahn Jung‐Min¹,Park Duk‐Woo¹,Lee Seung‐Whan¹,Kim Young‐Hak¹,Lee Cheol Whan¹,Park Seong‐Wook¹,Park Seung‐Jung¹

Affiliation:

1. Department of Cardiology University of Ulsan College of Medicine Asan Medical Center Seoul Korea

2. Biomedical Engineering Research Center Asan Institute for Life Sciences Seoul Korea

3. Department of Cardiology CHA Bundang Medical Center CHA University Seongnam Korea

4. Department of Cardiology Ajou University Suwon Korea

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

Reference19 articles.

1. Measurement of Fractional Flow Reserve to Assess the Functional Severity of Coronary-Artery Stenoses

2. Angiographic Versus Functional Severity of Coronary Artery Stenoses in the FAME Study

3. Fractional Flow Reserve versus Angiography for Guiding Percutaneous Coronary Intervention

4. Revascularization Decisions in Patients With Stable Angina and Intermediate Lesions

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