Improved nonparametric survival prediction using CoxPH, Random Survival Forest & DeepHit Neural Network

Abstract In recent times, time-to-event data such as time to failure or death is routinely collected alongside high-throughput covariates. These high-dimensional bioinformatics data often challenge classical survival models, which are either infeasible to fit or produce low prediction accuracy due t...

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Bibliographic Details

Published in:	BMC Medical Informatics and Decision Making
Main Authors:	Naseem Asghar, Umair Khalil, Basheer Ahmad, Huda M. Alshanbari, Muhammad Hamraz, Bakhtiyar Ahmad, Dost Muhammad Khan
Format:	Article
Language:	English
Published:	BMC 2024-05-01
Subjects:	CoxPH DeepHit Neural Network Machine learning Survival analysis High-dimensional data Feature selection
Online Access:	https://doi.org/10.1186/s12911-024-02525-z