Enabling Pre-Shock State Detection using Electrogram Signals from Implantable Cardioverter-Defibrillators-Reference-Cited by-同舟云学术

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Enabling Pre-Shock State Detection using Electrogram Signals from Implantable Cardioverter-Defibrillators

Published:2024-05-13 Issue: Volume: Page:1138-1141
ISSN:
Container-title:Companion Proceedings of the ACM Web Conference 2024
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Author:

Yan Runze¹^ORCID,Bhatia Neal K.²^ORCID,Merchant Faisal M.²^ORCID,Fedorov Alex¹^ORCID,Xiao Ran¹^ORCID,Ding Cheng³^ORCID,Hu Xiao¹^ORCID

Affiliation:

1. Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA

2. School of Medicine, Emory University, Atlanta, Georgia, USA

3. Department of Biomedical Engineering, Georgia Institution of Technology & Emory University, Atlanta, Georgia, USA

Funder

NIH (National Institutes of Health)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589335.3651450

Reference10 articles.

1. ICD lead proarrhythmia cured by lead extraction

2. The Entirely Subcutaneous Implantable Cardioverter-Defibrillator

3. Prediction of Sudden Cardiac Death in Implantable Cardioverter Defibrillators: A Review and Comparative Study of Heart Rate Variability Features

4. Jonathan Waring, Charlotta Lindvall, and Renato Umeton. Automated machine learning: Review of the state-of-the-art and opportunities for healthcare. Artificial intelligence in medicine, 104:101822, 2020.

5. Artificial Intelligence in Cardiology: Present and Future

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