Statistical models versus machine learning for competing risks: development and validation of prognostic models

Statistical models versus machine learning for competing risks: development and validation of prognostic models

Abstract Background In health research, several chronic diseases are susceptible to competing risks (CRs). Initially, statistical models (SM) were developed to estimate the cumulative incidence of an event in the presence of CRs. As recently there is a growing interest in applying machine learning (...

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Bibliographic Details
Main Authors: Georgios Kantidakis, Hein Putter, Saskia Litière, Marta Fiocco
Format: Article
Language:English
Published: BMC 2023-02-01
Series:BMC Medical Research Methodology
Subjects:
Artificial neural networks
Competing risks
Predictive performance
Random survival forests
Regression models
Supervised machine learning
Online Access:https://doi.org/10.1186/s12874-023-01866-z

Internet

https://doi.org/10.1186/s12874-023-01866-z

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