Deep learning for the dynamic prediction of multivariate longitudinal and survival data

DOI10.1002/SIM.9392zbMATH Open1547.62328MaRDI QIDQ6628599

Sheng Luo, Jeffrey Lin

Publication date: 29 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

joint modelfunctional data analysispersonalized medicineAlzheimer's diseasetemporal convolutionstransformer neural network

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data
• Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time‐to‐event in presence of censoring and competing risks
• Multivariate Functional Principal Component Analysis for Data Observed on Different (Dimensional) Domains
• Functional Data Analysis for Sparse Longitudinal Data
• Dynamic prediction of Alzheimer's disease progression using features of multiple longitudinal outcomes and time-to-event data

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