Data-driven modelling of neurodegenerative disease progression: thinking outside the black box
Data-driven disease progression models are an emerging set of computational tools that
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
Neurodegenerative disease of the brain: a survey of interdisciplinary approaches
F Davenport, J Gallacher, Z Kourtzi… - Journal of the …, 2023 - royalsocietypublishing.org
Neurodegenerative diseases of the brain pose a major and increasing global health
challenge, with only limited progress made in developing effective therapies over the last …
challenge, with only limited progress made in developing effective therapies over the last …
Educational attainment, structural brain reserve and Alzheimer's disease: a Mendelian randomization analysis
Higher educational attainment is observationally associated with lower risk of Alzheimer's
disease. However, the biological mechanisms underpinning this association remain unclear …
disease. However, the biological mechanisms underpinning this association remain unclear …
[HTML][HTML] Disease progression modelling of Alzheimer's disease using probabilistic principal components analysis
The recent biological redefinition of Alzheimer's Disease (AD) has spurred the development
of statistical models that relate changes in biomarkers with neurodegeneration and …
of statistical models that relate changes in biomarkers with neurodegeneration and …
[HTML][HTML] Forecasting individual progression trajectories in Alzheimer's disease
The anticipation of progression of Alzheimer's disease (AD) is crucial for evaluations of
secondary prevention measures thought to modify the disease trajectory. However, it is …
secondary prevention measures thought to modify the disease trajectory. However, it is …
[HTML][HTML] Bridging scales in Alzheimer's disease: biological framework for brain simulation with the virtual brain
Despite the acceleration of knowledge and data accumulation in neuroscience over the last
years, the highly prevalent neurodegenerative disease of AD remains a growing problem …
years, the highly prevalent neurodegenerative disease of AD remains a growing problem …
Progression models for imaging data with longitudinal variational auto encoders
B Sauty, S Durrleman - … Conference on Medical Image Computing and …, 2022 - Springer
Disease progression models are crucial to understanding degenerative diseases. Mixed-
effects models have been consistently used to model clinical assessments or biomarkers …
effects models have been consistently used to model clinical assessments or biomarkers …
[HTML][HTML] Forecasting individual progression trajectories in Huntington disease enables more powered clinical trials
Variability in neurodegenerative disease progression poses great challenges for the
evaluation of potential treatments. Identifying the persons who will experience significant …
evaluation of potential treatments. Identifying the persons who will experience significant …
[HTML][HTML] Combat harmonization: Empirical bayes versus fully bayes approaches
M Reynolds, T Chaudhary, ME Torbati… - NeuroImage: Clinical, 2023 - Elsevier
Studying small effects or subtle neuroanatomical variation requires large-scale sample size
data. As a result, combining neuroimaging data from multiple datasets is necessary …
data. As a result, combining neuroimaging data from multiple datasets is necessary …
The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022
DP Veitch, MW Weiner, M Miller, PS Aisen… - Alzheimer's & …, 2024 - Wiley Online Library
Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve
Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging …
Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging …