An artificial intelligence framework for improving predictive performance of left ventricular hypertrophy using electrocardiography-Reference-Cited by-同舟云学术

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An artificial intelligence framework for improving predictive performance of left ventricular hypertrophy using electrocardiography

Published:2022-02-06 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Electronics, Information, and Communication (ICEIC)
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Author:

Ryu Jiseung¹,Lee Yerin¹,Kang Hyunyoung¹,Lee Solam²,Park Youngjun³,Yang Sejung¹

Affiliation:

1. Yonsei University,Department of Biomedical Engineering,Wonju,Republic of Korea

2. Yonsei University Wonju College of Medicine,Department of Dermatology and Institute of Hair and Cosmetic Medicine, Department of Preventive Medicine,Wonju,Republic of Korea

3. Yonsei University,Division of Cardiology,Department of Internal Medicine, Wonju Severance Christian Hospita,Wonju,Republic of Korea

Funder

MSIT

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9748174/9748152/09748483.pdf?arnumber=9748483

Reference7 articles.

1. Improvement of electrocardiographic diagnostic accuracy of left ventricular hypertrophy using a Machine Learning approach

2. Electrocardiographic left ventricular hypertrophy and the risk of adverse cardiovascular events: A critical appraisal

3. Machine learning-based left ventricular hypertrophy detection using multi-lead ECG signal

4. Left Ventricular Hypertrophy by the Surface ECG

5. Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography

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