September 5, 2025Genomics & InformaticsOpen Access

Statistical learning methods for improving predictive performance in time-dependent survival models

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Refining time intervals improved the predictive accuracy of survival models in COVID-19.
Applying a stratified Cox PH model revealed a previously reported hazard ratio refinement.
Machine learning and deep learning models showed limited performance compared to the Cox PH model under certain conditions.
Events analyzed focused on death risk among infected versus uninfected individuals using UK Biobank data.

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Stratified Cox PH model enhances predictive accuracy in survival models, suggesting better assessment of time-dependent effects.

Seo et al. (2025) studied this question.

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