ArticleNeuroImage. Clinical2019
Multi-study validation of data-driven disease progression models to characterize evolution of biomarkers in Alzheimer's disease.
Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- ATN Classification and Machine-Learned Plasma Biomarker Phenotypes Reveal Distinct Alzheimer's Pathology in a Population-Based Cohort.medRxiv : the preprint server for health sciences · 2026Article
- Artificial intelligence in drug development for delirium and Alzheimer's disease.Acta pharmaceutica Sinica. B · 2025Review
- Stage-Aware Event-Based Modeling (SA-EBM) for Disease Progression.Proceedings of machine learning research · 2025Article
- Independent validation and outlier analysis of EuroPOND alzheimer's disease staging model using ADNI and real-world clinical data.Alzheimer's research & therapy · 2025Article
- The Potential of Disease Progression Modeling to Advance Clinical Development and Decision Making.Clinical pharmacology and therapeutics · 2025Review
- The Consortium for Clarity in ADRD Research Through Imaging (CLARiTI).Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Understanding the Temporal Dynamics of Accelerated Brain Aging and Resilient Brain Aging: Insights from Discriminative Event-Based Analysis of UK Biobank Data.Bioengineering (Basel, Switzerland) · 2024Article
- Data-driven modelling of neurodegenerative disease progression: thinking outside the black box.Nature reviews. Neuroscience · 2024Review
- Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA.Scientific reports · 2023Article
- The temporal event-based model: Learning event timelines in progressive diseases.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- Forecasting individual progression trajectories in Alzheimer's disease.Nature communications · 2023Article
- Current Applications of Machine Learning in Spine: From Clinical View.Global spine journal · 2022Review
- Diagnostic accuracy study of automated stratification of Alzheimer's disease and mild cognitive impairment via deep learning based on MRI.Annals of translational medicine · 2022Article
- A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia.Brain : a journal of neurology · 2022Article
- Comparison and aggregation of event sequences across ten cohorts to describe the consensus biomarker evolution in Alzheimer's disease.Alzheimer's research & therapy · 2022Article
- Disruption of the grid cell network in a mouse model of early Alzheimer's disease.Nature communications · 2022Article
- Modifiable risk factors for dementia and dementia risk profiling. A user manual for Brain Health Services-part 2 of 6.Alzheimer's research & therapy · 2021Review
- AD Course Map charts Alzheimer's disease progression.Scientific reports · 2021Article
- Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2021Review
- Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease.Frontiers in big data · 2021Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Understanding the sequence of biological and clinical events along the course of Alzheimer's disease provides insights into dementia pathophysiology and can help participant selection in clinical trials. Our objective is to train two data-driven computational models for sequencing these events, the Event Based Model (EBM) and discriminative-EBM (DEBM), on the basis of well-characterized research data, then validate the trained models on subjects from clinical cohorts characterized by less-structured data-acquisition protocols. Seven independent data cohorts were considered totalling 2389 cognitively normal (CN), 1424 mild cognitive impairment (MCI) and 743 Alzheimer's disease (AD) patients. The Alzheimer's Disease Neuroimaging Initiative (ADNI) data set was used as training set for the constriction of disease models while a collection of multi-centric data cohorts was used as test set for validation. Cross-sectional information related to clinical, cognitive, imaging and cerebrospinal fluid (CSF) biomarkers was used. Event sequences obtained with EBM and DEBM showed differences in the ordering of single biomarkers but according to both the first biomarkers to become abnormal were those related to CSF, followed by cognitive scores, while structural imaging showed significant volumetric decreases at later stages of the disease progression. Staging of test set subjects based on sequences obtained with both models showed good linear correlation with the Mini Mental State Examination score (R
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