Improvement of electrocardiographic diagnostic accuracy of left ventricular hypertrophy using a Machine Learning approach

The electrocardiogram (ECG) is the most common tool used to predict left ventricular hypertrophy (LVH). However, it is limited by its low accuracy (<60%) and sensitivity (30%). We set forth the hypothesis that the Machine Learning (ML) C5.0 algorithm could optimize the ECG in the prediction of LV...

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Detalles Bibliográficos
Autores principales: De la Garza-Salazar, Fernando, Romero-Ibarguengoitia, Maria Elena, Rodriguez-Diaz, Elias Abraham, Azpiri-Lopez, Jose Ramón, González-Cantu, Arnulfo
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/PMC7219774/
https://www.ncbi.nlm.nih.gov/pubmed/32401764
http://dx.doi.org/10.1371/journal.pone.0232657

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219774/
https://www.ncbi.nlm.nih.gov/pubmed/32401764
http://dx.doi.org/10.1371/journal.pone.0232657

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