Identifying ALS Disease Progression Subtypes
Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that is heterogeneous in its onset, pattern of spread, and disease progression. Here we have established a Mixture of Gaussian Processes model to identify disease progression clusters from sparse longitudinal clinical data. We show that clusters can follow nonlinear trajectory patterns, are robust to sparse data, and correspond with survival outcomes. Our results characterize the complex disease progression patterns of ALS.