DP-MoSt fits continuous sigmoidal disease trajectories and uses a two-level mixture to identify which biomarkers split into sub-trajectories and which patients belong to each subgroup.
European Journal of Neuro- science 49(3), 328–338 (2019)
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Disease Progression Modelling and Stratification for detecting sub-trajectories in the natural history of pathologies: application to Parkinson's Disease trajectory modelling
DP-MoSt fits continuous sigmoidal disease trajectories and uses a two-level mixture to identify which biomarkers split into sub-trajectories and which patients belong to each subgroup.