Multivariate longitudinal data for survival analysis of cardiovascular event prediction in young adults: insights from a comparative explainable study

Multivariate longitudinal data for survival analysis of cardiovascular event prediction in young adults: insights from a comparative explainable study

Abstract Background Multivariate longitudinal data are under-utilized for survival analysis compared to cross-sectional data (CS - data collected once across cohort). Particularly in cardiovascular risk prediction, despite available methods of longitudinal data analysis, the value of longitudinal in...

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Bibliographic Details
Main Authors: Hieu T. Nguyen, Henrique D. Vasconcellos, Kimberley Keck, Jared P. Reis, Cora E. Lewis, Steven Sidney, Donald M. Lloyd-Jones, Pamela J. Schreiner, Eliseo Guallar, Colin O. Wu, João A.C. Lima, Bharath Ambale-Venkatesh
Format: Article
Language:English
Published: BMC 2023-01-01
Series:BMC Medical Research Methodology
Subjects:
Longitudinal data
Explainable AI
Survival analysis
Risk prediction
Repeated measures
Personalized medicine
Online Access:https://doi.org/10.1186/s12874-023-01845-4

Internet

https://doi.org/10.1186/s12874-023-01845-4

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