Comparison of Machine Learning Techniques for Prediction of Hospitalization in Heart Failure Patients

Comparison of Machine Learning Techniques for Prediction of Hospitalization in Heart Failure Patients

The present study aims to compare the performance of eight Machine Learning Techniques (MLTs) in the prediction of hospitalization among patients with heart failure, using data from the Gestione Integrata dello Scompenso Cardiaco (GISC) study. The GISC project is an ongoing study that takes place in...

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Bibliographic Details
Main Authors: Giulia Lorenzoni, Stefano Santo Sabato, Corrado Lanera, Daniele Bottigliengo, Clara Minto, Honoria Ocagli, Paola De Paolis, Dario Gregori, Sabino Iliceto, Franco Pisanò
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Journal of Clinical Medicine
Subjects:
heart failure
machine learning techniques
hospitalization
Online Access:https://www.mdpi.com/2077-0383/8/9/1298

Internet

https://www.mdpi.com/2077-0383/8/9/1298

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