Literature DB >> 31668636

Deep learning to automatically interpret images of the electrocardiogram: Do we need the raw samples?

Rob Brisk1, Raymond Bond2, Elizabeth Banks3, Alicja Piadlo4, Dewar Finlay5, James McLaughlin5, David McEneaney3.   

Abstract

Mesh：

Year:  2019        PMID： 31668636     DOI： 10.1016/j.jelectrocard.2019.09.018

Source DB:  PubMed          Journal:  J Electrocardiol        ISSN： 0022-0736            Impact factor:   1.438


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  4 in total

1.  Digitizing ECG image: A new method and open-source software code.

Authors:  Julian D Fortune; Natalie E Coppa; Kazi T Haq; Hetal Patel; Larisa G Tereshchenko
Journal:  Comput Methods Programs Biomed       Date:  2022-05-14       Impact factor: 7.027

2.  Artificial intelligence to detect abnormal heart rhythm from scanned electrocardiogram tracings.

Authors:  Joshua Bridge; Lu Fu; Weidong Lin; Yumei Xue; Gregory Y H Lip; Yalin Zheng
Journal:  J Arrhythm       Date:  2022-03-29

3.  Deep learning and the electrocardiogram: review of the current state-of-the-art.

Authors:  Sulaiman Somani; Adam J Russak; Felix Richter; Shan Zhao; Akhil Vaid; Fayzan Chaudhry; Jessica K De Freitas; Nidhi Naik; Riccardio Miotto; Girish N Nadkarni; Jagat Narula; Edgar Argulian; Benjamin S Glicksberg
Journal:  Europace       Date:  2021-02-10       Impact factor: 5.214

4.  WaSP-ECG: A Wave Segmentation Pretraining Toolkit for Electrocardiogram Analysis.

Authors:  Rob Brisk; Raymond R Bond; Dewar Finlay; James A D McLaughlin; Alicja J Piadlo; David J McEneaney
Journal:  Front Physiol       Date:  2022-03-17       Impact factor: 4.566
  4 in total

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