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

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...

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Bibliographic Details
Main Authors: Cristina Lopez, Jose Luis Holgado, Raquel Cortes, Inma Sauri, Antonio Fernandez, Jose Miguel Calderon, Julio Nuñez, Josep Redon
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Bioengineering
Subjects:
heart failure
phenotype
left ventricular ejection fraction
primary care
artificial intelligence
supervised analysis
Online Access:https://www.mdpi.com/2306-5354/8/6/85

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https://www.mdpi.com/2306-5354/8/6/85

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