Performance of a Convolutional Neural Network and Explainability Technique for 12-Lead Electrocardiogram Interpretation-Reference-Cited by-同舟云学术

Performance of a Convolutional Neural Network and Explainability Technique for 12-Lead Electrocardiogram Interpretation

Published:2021-11-01 Issue:11 Volume:6 Page:1285
ISSN:2380-6583
Container-title:JAMA Cardiology
language:en
Short-container-title:JAMA Cardiol

Author:

Hughes J. Weston¹,Olgin Jeffrey E.²³,Avram Robert²³,Abreau Sean A.²³,Sittler Taylor⁴,Radia Kaahan¹,Hsia Henry²,Walters Tomos²,Lee Byron²,Gonzalez Joseph E.¹,Tison Geoffrey H.¹²³⁵

Affiliation:

1. RISE Lab, Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley

2. Department of Medicine, Division of Cardiology, University of California, San Francisco, San Francisco

3. Cardiovascular Research Institute, San Francisco, California

4. Department of Laboratory Medicine, University of California, San Francisco, San Francisco

5. Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco

Publisher

American Medical Association (AMA)

Subject

Cardiology and Cardiovascular Medicine

Link

https://jamanetwork.com/journals/jamacardiology/articlepdf/2782549/jamacardiology_hughes_2021_oi_210051_1635348688.2775.pdf

Reference29 articles.

1. Status of computerized electrocardiography.;Hongo;Cardiol Clin,2006

2. Computer-interpreted electrocardiograms: benefits and limitations.;Schläpfer;J Am Coll Cardiol,2017

3. The electrocardiogram in population studies. a classification system.;Blackburn;Circulation,1960

4. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.;Hannun;Nat Med,2019

5. Automatic diagnosis of the 12-lead ECG using a deep neural network.;Ribeiro;Nat Commun,2020

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