Demonstration of the potential of white-box machine learning approaches to gain insights from cardiovascular disease electrocardiograms

We present the results from a white-box machine learning approach to detect cardiac arrhythmias using electrocardiographic data. A C5.0 is trained to recognize four classes using common features. The four classes are (i) atrial fibrillation and atrial flutter, (ii) tachycardias (iii), sinus bradycar...

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Detalles Bibliográficos
Autores principales: Rieg, Thilo, Frick, Janek, Baumgartl, Hermann, Buettner, Ricardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746264/
https://www.ncbi.nlm.nih.gov/pubmed/33332440
http://dx.doi.org/10.1371/journal.pone.0243615

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746264/
https://www.ncbi.nlm.nih.gov/pubmed/33332440
http://dx.doi.org/10.1371/journal.pone.0243615

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