Data-Driven Disease Progression Modeling

Abstract

Abstract Intense debate in the neurology community before 2010 culminated in hypothetical models of Alzheimer’s disease progression: a pathophysiological cascade of biomarkers, each dynamic for only a segment of the full disease timeline. Inspired by this, data-driven disease progression modeling emerged from the computer science community with the aim to reconstruct neurodegenerative disease timelines using data from large cohorts of patients, healthy controls, and prodromal/at-risk individuals. This chapter describes selected highlights from the field, with a focus on utility for understanding and forecasting of disease progression.

Topics & Concepts