Identification of Electrocardiographic Patterns Related to Mortality with COVID-19

COVID-19 is an infectious disease that has greatly affected worldwide healthcare systems, due to the high number of cases and deaths. As COVID-19 patients may develop cardiac comorbidities that can be potentially fatal, electrocardiographic monitoring can be crucial. This work aims to identify elect...

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Veröffentlicht in:	Applied sciences Jg. 14; H. 2; S. 817
Hauptverfasser:	Sbrollini, Agnese, Leoni, Chiara, Morettini, Micaela, Rivolta, Massimo W., Swenne, Cees A., Mainardi, Luca, Burattini, Laura, Sassi, Roberto
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.01.2024
Schlagworte:	Advanced Repeated Structuring and Learning Procedure Algorithms Cardiac patients Cardiology Clinical medicine COVID-19 Deep learning Disease transmission Electric properties Electrocardiography Health aspects Heart failure Hospitalization Infections Ischemia local-interpretable model-agnostic explanations Machine learning Morphology Mortality neural network Neural networks Neurons Pandemics Respiratory system
ISSN:	2076-3417, 2076-3417
Online-Zugang:	Volltext
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