Electrocardiogram-based deep learning model to screen peripartum cardiomyopathy-Reference-Cited by-同舟云学术

Electrocardiogram-based deep learning model to screen peripartum cardiomyopathy

Published:2023-12 Issue:12 Volume:5 Page:101184
ISSN:2589-9333
Container-title:American Journal of Obstetrics & Gynecology MFM
language:en
Short-container-title:American Journal of Obstetrics & Gynecology MFM

Author:

Jung Young Mi,Kang Sora,Son Jeong Min,Lee Hak Seung,Han Ga In,Yoo Ah-Hyun,Kwon Joon-myoung,Park Chan-Wook,Park Joong Shin,Jun Jong Kwan,Lee Min Sung,Lee Seung Mi

Funder

Seoul National University Hospital

Publisher

Elsevier BV

Subject

General Medicine,Obstetrics and Gynecology

Reference23 articles.

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2. Peripartum cardiomyopathy: current management and future perspectives;Hilfiker-Kleiner;Eur Heart J,2015

3. Clinical characteristics and long-term predictors of persistent left ventricular systolic dysfunction in peripartum cardiomyopathy;Li;Can J Cardiol,2016

4. An artificial intelligence electrocardiogram analysis for detecting cardiomyopathy in the peripartum period;Lee;Int J Cardiol,2022

5. Detecting cardiomyopathies in pregnancy and the postpartum period with an electrocardiogram-based deep learning model;Adedinsewo;Eur Heart J Digit Health,2021

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