ArticleAging2020
Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression.
Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
15 citing papers in PubMed, 24 citations in OpenAlex.
- BAYESIAN LEARNING OF CLINICALLY MEANINGFUL SEPSIS PHENOTYPES IN NORTHERN TANZANIA.The annals of applied statistics · 2025Article
- Atrophy trajectories in Alzheimer's disease: how sex matters.Alzheimer's research & therapy · 2025Article
- Analyzing heterogeneity in Alzheimer disease using multimodal normative modeling on imaging-based ATN biomarkers.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Multivariate longitudinal clustering reveals neuropsychological factors as dementia predictors in an Alzheimer's disease progression study.BioData mining · 2025Article
- Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning.Biological psychiatry · 2024Review
- Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction.Scientific reports · 2024Article
- Article
- Divergent neurodegenerative patterns: Comparison of [Brain communications · 2024Article
- Fast three-dimensional image generation for healthy brain aging using diffeomorphic registration.Human brain mapping · 2023Article
- Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer's disease.Nature communications · 2022Article
- Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data.Alzheimer's research & therapy · 2022Article
- Multi-scale semi-supervised clustering of brain images: Deriving disease subtypes.Medical image analysis · 2022Article
- Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease.Frontiers in big data · 2021Article
- Longitudinal deterioration of white-matter integrity: heterogeneity in the ageing population.Brain communications · 2021Article
- Comparison of subtyping methods for neuroimaging studies in Alzheimer's disease: a call for harmonization.Brain communications · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
Abstract
Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathogenesis. We propose a framework for longitudinal clustering that simultaneously: 1) incorporates whole brain data, 2) leverages unequal visits per individual, 3) compares clusters with a control group, 4) allows for study confounding effects, 5) provides cluster visualization, 6) measures clustering uncertainty. We used amyloid-β positive AD and negative healthy subjects, three longitudinal structural magnetic resonance imaging scans (cortical thickness and subcortical volume) over two years. We found three distinct longitudinal AD brain atrophy patterns: one typical diffuse pattern (n=34, 47.2%), and two atypical patterns: minimal atrophy (n=23 31.9%) and hippocampal sparing (n=9, 12.5%). We also identified outliers (n=3, 4.2%) and observations with uncertain classification (n=3, 4.2%). The clusters differed not only in regional distributions of atrophy at baseline, but also longitudinal atrophy progression, age at AD onset, and cognitive decline. A framework for the longitudinal assessment of variability in cohorts with several neuroimaging measures was successfully developed. We believe this framework may aid in disentangling distinct subtypes of AD from disease staging.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.