Data-Driven Disease Progression Modelling

• URL: http://arxiv.org/abs/2211.05786v1
• Date: Tue, 1 Nov 2022 10:55:31 GMT
• Title: Data-Driven Disease Progression Modelling
• Authors: Neil P. Oxtoby
• Abstract summary: Data-driven disease progression modelling emerged from the computer science community. This chapter describes selected highlights from the field, with a focus on utility for understanding and forecasting of disease progression.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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 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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