ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2021
Predictive value of ATN biomarker profiles in estimating disease progression in Alzheimer's disease dementia.
Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Encoding Discordance in the Alzheimer's Disease A/T/N Framework.medRxiv : the preprint server for health sciences · 2026Article
- Explainable machine learning for the prediction of Alzheimer's disease-related cognitive impairment: a consensus feature selection approach.BMC medical informatics and decision making · 2026Article
- Striatal functional connectivity alterations in mild cognitive impairment subtypes defined by CSF A/T biomarkers.Frontiers in aging neuroscience · 2026Article
- Alterations in functional connectivity of the anterior cingulate cortex associated with different levels of tau and amyloid-Frontiers in neuroscience · 2026Article
- Predicting future cognitive impairment in preclinical Alzheimer's disease using multimodal imaging: a multisite machine learning study.medRxiv : the preprint server for health sciences · 2025Article
- Dual risk of anticholinergic burden and CSF alzheimer's biomarkers in older patients: a mortality follow-up study from daily medical practice.Alzheimer's research & therapy · 2025Article
- Cerebrospinal fluid inflammatory cytokines as prognostic indicators for cognitive decline across Alzheimer's disease spectrum.Journal of Alzheimer's disease : JAD · 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
- MRI-guided clustering of patients with mild dementia due to Alzheimer's disease using self-organizing maps.Neuroimage. Reports · 2024Article
- Evaluation of ComBat Harmonization for Reducing Across-Tracer Differences in Regional Amyloid PET Analyses.Human brain mapping · 2024Article
- Contributions of the ADNI Biostatistics Core.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Review
- Article
- A federated learning architecture for secure and private neuroimaging analysis.Patterns (New York, N.Y.) · 2024Article
- Deep learning-based amyloid PET harmonization to predict cognitive decline in non-demented elderly.Radiology advances · 2024Article
- Association Between β-Amyloid Accumulation and Incident Dementia in Individuals 80 Years or Older Without Dementia.Neurology · 2024Article
- AT(N) biomarker profiles and Alzheimer's disease symptomology in Down syndrome.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Review
- Plasma Biomarkers as Predictors of Progression to Dementia in Individuals with Mild Cognitive Impairment.Journal of Alzheimer's disease : JAD · 2024Article
- Exercise Intervention for Alzheimer's Disease: Unraveling Neurobiological Mechanisms and Assessing Effects.Life (Basel, Switzerland) · 2023Review
- Delayed and More Variable Unimanual and Bimanual Finger Tapping in Alzheimer's Disease: Associations with Biomarkers and Applications for Classification.Journal of Alzheimer's disease : JAD · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 415) we assessed predictive performance of ATN classification using empirical knowledge-based cut-offs for each component of ATN and compared it to two data-driven approaches, logistic regression and RUSBoost machine learning classifiers, which used continuous clinical or biomarker scores. In data-driven approaches, we identified ATN features that distinguish normals from individuals with dementia and used them to classify persons with MCI into dementia-like and normal groups. Both data-driven classification methods performed better than the empirical cut-offs for ATN biomarkers in predicting conversion to dementia. Classifiers that used clinical features performed as well as classifiers that used ATN biomarkers for prediction of progression to dementia. We discuss that data-driven modeling approaches can improve our ability to predict disease progression and might have implications in future clinical trials.
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