Electrocardiogram Signal Analysis With a Machine Learning Model Predicts the Presence of Pulmonary Embolism With Accuracy Dependent on Embolism Burden-Reference-Cited by-同舟云学术

Electrocardiogram Signal Analysis With a Machine Learning Model Predicts the Presence of Pulmonary Embolism With Accuracy Dependent on Embolism Burden

Published:2024-09 Issue:3 Volume:2 Page:453-462
ISSN:2949-7612
Container-title:Mayo Clinic Proceedings: Digital Health
language:en
Short-container-title:Mayo Clinic Proceedings: Digital Health

Author:

Wysokinski Waldemar E.,Meverden Ryan A.,Lopez-Jimenez Francisco,Harmon David M.,Medina Inojosa Betsy J.,Suarez Abraham Baez,Liu Kan,Medina Inojosa Jose R.,Casanegra Ana I.,McBane Robert D.,Houghton Damon E.

Funder

Mayo Clinic

Publisher

Elsevier BV

Reference33 articles.

1. Reasons for the persistent incidence of venous thromboembolism;Heit;Thromb Haemost,2017

2. Stratification, imaging, and management of acute massive and submassive pulmonary embolism;Sista;Radiology,2017

3. U.S. trends in computed tomography use and diagnoses in emergency department visits by patients with symptoms suggestive of pulmonary embolism, 2001-2009;Feng;Acad Emerg Med,2013

4. Over-testing for suspected pulmonary embolism in American emergency departments: the continuing epidemic;Kline;Circ Cardiovasc Qual Outcomes,2020

5. Management of massive and submassive pulmonary embolism, iliofemoral deep vein thrombosis, and chronic thromboembolic pulmonary hypertension: a scientific statement from the American Heart Association;Jaff;Circulation,2011

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