A Gandy: Department of Mathematics, Imperial College London, U.K. T Matcham: Department of Mathematics, Imperial College London, U.K. and NIHR ARC Northwest London, U.K.
Overview
The paper suggests using the hazard rate as the time-varying risk score when calculating concordance. Through
simulations it is demonstrated situations in which other concordance indices can lead to incorrect models being selected over a true model, justifying the use of the
risk prediction in both model selection and loss functions in, e.g., deep learning models
Contributions and Distinctions from Previous Works
Methods
Survival analysis
Results
Cite
Comments
Chapter 6 uses DeepHit code from https://github.com/chl8856/DeepHit with changes made to also include their concordance index in the loss and validation.
TL;DR
This paper proposes a concordance index for time-varying risks
Paper Link
https://doi.org/10.48550/arXiv.2208.03213
Author/Institution
A Gandy: Department of Mathematics, Imperial College London, U.K. T Matcham: Department of Mathematics, Imperial College London, U.K. and NIHR ARC Northwest London, U.K.
Overview
The paper suggests using the hazard rate as the time-varying risk score when calculating concordance. Through simulations it is demonstrated situations in which other concordance indices can lead to incorrect models being selected over a true model, justifying the use of the risk prediction in both model selection and loss functions in, e.g., deep learning models
Contributions and Distinctions from Previous Works
Methods
Survival analysis
Results
Cite
Comments
Chapter 6 uses DeepHit code from https://github.com/chl8856/DeepHit with changes made to also include their concordance index in the loss and validation.
https://github.com/tmatcham/CrossingHazardConcordance