Supervised Analysis for Phenotype Identification: The Case of Heart Failure Ejection Fraction Class

Artificial Intelligence is creating a paradigm shift in health care, with phenotyping patients through clustering techniques being one of the areas of interest. Objective: To develop a predictive model to classify heart failure (HF) patients according to their left ventricular ejection fraction (LVE...

Descripción completa

Detalles Bibliográficos
Autores principales: Lopez, Cristina, Holgado, Jose Luis, Cortes, Raquel, Sauri, Inma, Fernandez, Antonio, Calderon, Jose Miguel, Nuñez, Julio, Redon, Josep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233943/
https://www.ncbi.nlm.nih.gov/pubmed/34205745
http://dx.doi.org/10.3390/bioengineering8060085

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233943/
https://www.ncbi.nlm.nih.gov/pubmed/34205745
http://dx.doi.org/10.3390/bioengineering8060085

Ejemplares similares