A machine learning-based approach to identify peripheral artery disease using texture features from contrast-enhanced magnetic resonance imaging

Author:

Khagi Bijen,Belousova Tatiana,Short Christina M.,Taylor Addison,Nambi Vijay,Ballantyne Christie M.,Bismuth Jean,Shah Dipan J.,Brunner Gerd

Funder

American Heart Association

National Institutes of Health

National Heart Lung and Blood Institute

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,Biomedical Engineering,Biophysics

Reference48 articles.

1. Burden of peripheral artery disease and its attributable risk factors in 204 countries and territories from 1990 to 2019;Lin;Front Cardiovasc Med,2022

2. Heart disease and stroke Statistics-2021 update: a report from the American Heart Association;Virani;Circulation,2021

3. Arterial diseases of the extremities;Creager,2018

4. Diagnosis and management of diseases of the peripheral arteries;Cohoon,2017

5. The use of machine learning for the identification of peripheral artery disease and future mortality risk;Ross;J Vasc Surg,2016

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