In this project we introduce and illustarte the framework of optimal biomarkers for the description of stochastic disease dynamics. The framework is illustrated by analysing longitudinal dataset of patient recovery dynamics after kidney transplant. We provide a gentle intoduction into the methodology behind the approach and illustrate supervised and non-spervised determination of optimal biomarkers. We also discuss regularization.
krivovsv/biomarker
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