Data-Driven Disease Progression Modelling. (arXiv:2211.05786v1 [q-bio.NC])

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 modelling 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.



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