Прогнозування кардіоміопатії у пацієнтів з постійною шлуночковою електрокардіостимуляцією за допомогою методів машинного навчання

Pacing-induced cardiomyopathy is a notable issue in patients needing permanent ventricular pacing. Identifying risk groups early and swiftly preventing the ailment can reduce patient harm. However, current prognostic methods require clarity. We employed machine learning to develop predictive models...

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Bibliographic Details
Date:2024
Author Affiliations:
  • Eugene Perepeka — Amosov National Institute of Cardiovascular Surgery, Kyiv
  • Vasyl Lazoryshynets — Amosov National Institute of Cardiovascular Surgery, Kyiv
  • Vitalii Babenko — National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv
  • Illia Davydovych — National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv
  • Ievgen Nastenko — National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv
Keywords:keywords
Main Authors: Perepeka, Eugene, Lazoryshynets, Vasyl, Babenko, Vitalii, Davydovych, Illia, Nastenko, Ievgen
Format: Article
Language:English
Published: The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2024
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Online Access:https://journal.iasa.kpi.ua/article/view/285956
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Journal Title:System research and information technologies
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System research and information technologies