EventsMOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed.
Published
with-doi10.3390/mol2net-06-08980 (registering DOI)
This submission belongs to the session 05. BIOMEDIT-01; ITCs & Biomol. Biomed. Eng. Workshop, Lund, Sweden, Chengdu, China, New Orleans, USA, 2020 of the event MOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed.
Published date
08 Jan, 2021
Citation
Shoujing Wang, Bairong Shen, Cesar Augusto Martin, Signal Analysis of Heart Rate Variability and Applications on the Diagnosis of Cardiovascular Diseases, in Proceedings of MOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed., 30 January 2020–30 January 2021, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-06-08980
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Signal Analysis of Heart Rate Variability and Applications on the Diagnosis of Cardiovascular Diseases

1. a Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China. b University of the Basque Country UPV/EHU, Bilbao, Biscay, Spain
2. Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China
3. University of the Basque Country UPV/EHU, Bilbao, Biscay, Spain
Abstract

The electrocardiogram (ECG) is a fundamental tool in daily clinical medicine practice, recording millions of ECGs annually. Computer-assisted interpretation is becoming more and more important in clinical ECG processing and interpretation, serving as a crucial adjunct to physician interpretation in many clinical settings. But the existing commercial ECG interpretation algorithms still show substantial rates of misdiagnosis, and there is still a lack of comprehensive evaluation of computer-aided interpretation. We recommend using an ensemble method to process and classify clinical ECGs for providing accuracy and increasing rhythm classes.

Keywords
Electrocardiogram
Cardiovascular Diseases
classification
Manuscript
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