ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2019
Accurate risk estimation of β-amyloid positivity to identify prodromal Alzheimer's disease: Cross-validation study of practical algorithms.
Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Predicting Brain Amyloid PET Positivity Using the Amyloid Beta Composite (ABC) Index in Patients With Cognitive Impairment.Dementia and neurocognitive disorders · 2026Article
- Deep Learning-Based Prediction of PET Amyloid Status Using MRI.AJNR. American journal of neuroradiology · 2025Article
- Diagnostic and prognostic multimodal prediction models in Alzheimer's disease: A scoping review.Journal of Alzheimer's disease : JAD · 2025Article
- AI-driven fusion of multimodal data for Alzheimer's disease biomarker assessment.Nature communications · 2025Article
- Development of Simple Risk Scores for Prediction of Brain β-Amyloid and Tau Status in Older Adults With Mild Cognitive Impairment: A Machine Learning Approach.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025Article
- Alzheimer's disease neuropathology and its estimation with fluid and imaging biomarkers.Molecular neurodegeneration · 2025Review
- Predicting amyloid beta accumulation in cognitively unimpaired older adults: Cognitive assessments provide no additional utility beyond demographic and genetic factors.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study.Alzheimer's research & therapy · 2025Observational
- New Research on Biomarkers in Alzheimer's Continuum.Reviews on recent clinical trials · 2025Review
- Diagnosis of Alzheimer's disease using plasma biomarkers adjusted to clinical probability.Nature aging · 2024Article
- Development and assessment of algorithms for predicting brain amyloid positivity in a population without dementia.Alzheimer's research & therapy · 2024Article
- Understanding machine learning applications in dementia research and clinical practice: a review for biomedical scientists and clinicians.Alzheimer's research & therapy · 2024Review
- Acceptable performance of blood biomarker tests of amyloid pathology - recommendations from the Global CEO Initiative on Alzheimer's Disease.Nature reviews. Neurology · 2024Review
- Associations of modifiable and non-modifiable risk factors with cognitive functions - a prospective, population-based, 17 years follow-up study of 3,229 individuals.Alzheimer's research & therapy · 2024Article
- Machine learning prediction of future amyloid beta positivity in amyloid-negative individuals.Alzheimer's research & therapy · 2024Article
- Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET.PloS one · 2024Article
- Examining the diagnostic value of the mnemonic discrimination task for classification of cognitive status and amyloid-beta burden.Neuropsychologia · 2023Article
- Predicting positron emission tomography brain amyloid positivity using interpretable machine learning models with wearable sensor data and lifestyle factors.Alzheimer's research & therapy · 2023Observational
- A Stable and Scalable Digital Composite Neurocognitive Test for Early Dementia Screening Based on Machine Learning: Model Development and Validation Study.Journal of medical Internet research · 2023Article
- Predicting amyloid-beta pathology in the general population.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023Article
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Authors and funding
10 authors.
Funding
Abstract
introductionThe aim was to create readily available algorithms that estimate the individual risk of β-amyloid (Aβ) positivity.
methodsThe algorithms were tested in BioFINDER (n = 391, subjective cognitive decline or mild cognitive impairment) and validated in Alzheimer's Disease Neuroimaging Initiative (n = 661, subjective cognitive decline or mild cognitive impairment). The examined predictors of Aβ status were demographics; cognitive tests; white matter lesions; apolipoprotein E (APOE); and plasma Aβ
resultsAβ status was accurately estimated in BioFINDER using age, 10-word delayed recall or Mini-Mental State Examination, and APOE (area under the receiver operating characteristics curve = 0.81 [0.77-0.85] to 0.83 [0.79-0.87]). When validated, the models performed almost identical in Alzheimer's Disease Neuroimaging Initiative (area under the receiver operating characteristics curve = 0.80-0.82) and within different age, subjective cognitive decline, and mild cognitive impairment populations. Plasma Aβ DISCUSSION: The algorithms are implemented on http://amyloidrisk.com where the individual probability of being Aβ positive can be calculated. This is useful in the workup of prodromal Alzheimer's disease and can reduce the number needed to screen in Alzheimer's disease trials.
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