Comparing ECG Lead Subsets for Heart Arrhythmia/ECG Pattern Classification: Convolutional Neural Networks and Random Forest

Optimal ECG lead subsets provide classification accuracy similar to that using all 12 leads across DL and CML methods. The DL method achieved slightly higher classification accuracy on larger data sets and required fewer ECG leads compared with the CML method.

Authors

Shijie Zhou (ORCID: https://orcid.org/0000-0002-6082-8921)
John Whitaker (ORCID: https://orcid.org/0000-0002-5361-5725)
Zixuan Ni (ORCID: https://orcid.org/0000-0001-5196-983X)
Serhii Reznichenko

Institutions

Worcester Polytechnic Institute (US)
Guy's and St Thomas' NHS Foundation Trust (GB)
Miami University (US)

Publication Details

Journal: CJC Open
Published: 2024-11-08
DOI: https://doi.org/10.1016/j.cjco.2024.10.012
Citations: 7
Primary Topic: ECG Monitoring and Analysis
Type: article
Field-Weighted Citation Impact: 2.81

Funders

American Heart Association
National Institutes of Health
National Heart, Lung, and Blood Institute

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article

Comparing ECG Lead Subsets for Heart Arrhythmia/ECG Pattern Classification: Convolutional Neural Networks and Random Forest

Shijie Zhou, John Whitaker, Zixuan Ni, Serhii Reznichenko

Nov 8, 2024

7 citations

CJC Open

ECG Monitoring and Analysis

2.81

article

Comparing ECG Lead Subsets for Heart Arrhythmia/ECG Pattern Classification: Convolutional Neural Networks and Random Forest

Shijie Zhou, John Whitaker, Zixuan Ni, Serhii Reznichenko

November 8, 2024article en

7 citations

Abstract

Optimal ECG lead subsets provide classification accuracy similar to that using all 12 leads across DL and CML methods. The DL method achieved slightly higher classification accuracy on larger data sets and required fewer ECG leads compared with the CML method.

CJC OpenVol. 7(2)

Worcester Polytechnic Institute (US), Guy's and St Thomas' NHS Foundation Trust (GB), Miami University (US)

American Heart Association, National Institutes of Health, National Heart, Lung, and Blood Institute

Life in Land

Openalex Percentile: Top 8%

ECG Monitoring and Analysis

2.81

DOI Open Access PDF OpenAlex

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Comparing ECG Lead Subsets for Heart Arrhythmia/ECG Pattern Classification: Convolutional Neural Networks and Random Forest — Shijie Zhou, John Whitaker, et al. · CJC Open (2024) | TGRS Research Map | TGRS