Disease Progression Modeling and Stratification for detecting sub-trajectories in the natural history of pathologies: Application to Alzheimer's disease trajectory modeling.

ABSTRACT: Quantifying the progression of degenerative diseases remains crucial for early diagnosis, prevention, and treatment. However, accurately modeling disease biomarker evolution is hindered by substantial variability in disease trajectories among individuals, driven by demographic, genetic, and lifestyle factors. This variability gives rise to heterogeneous phenotypic manifestations, underscoring the need for stratification based on underlying disease subtypes. Recent advances have shown promise in unsupervised stratification of disease trajectories. Yet, current approaches face significant challenges related to robustness, biomarker specificity, interpretability, and temporal resolution of clustering results. To address these challenges, we introduce Disease Progression Modeling and Stratific

SUBMITTER: Viani A 

PROVIDER: S-EPMC12592369 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature