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Optimizing dynamic predictions from joint models using super learning
Joint models for longitudinal and timeātoāevent data are often employed to calculate dynamic individualized predictions used in numerous applications of precision medicine. Two components of joint models that influence the accuracy of these predictions are the shape of the longitudinal trajectories and the functional form linking the longitudinal outcome history ā¦