A functional Cox model is developed for interval-censored data using penalized maximum likelihood estimation via an EM algorithm, with proofs of consistency, asymptotic normality, and semiparametric efficiency, plus a global test for the functional covariate effect.
et al.: The UK Biobank resource with deep phenotyping and genomic data
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Disease trajectory embeddings from longitudinal EHR data serve as structural priors to enhance multi-organ IDP representation learning, improving AUC and MAE for disease prediction across 159 conditions in UK Biobank.
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Functional Cox model for interval-censored data
A functional Cox model is developed for interval-censored data using penalized maximum likelihood estimation via an EM algorithm, with proofs of consistency, asymptotic normality, and semiparametric efficiency, plus a global test for the functional covariate effect.
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From Trajectories to Phenotypes: Disease Progression as Structural Priors for Multi-organ Imaging Representation Learning
Disease trajectory embeddings from longitudinal EHR data serve as structural priors to enhance multi-organ IDP representation learning, improving AUC and MAE for disease prediction across 159 conditions in UK Biobank.