ArticleAlzheimer's & dementia (New York, N. Y.)2021
Predicting amyloid risk by machine learning algorithms based on the A4 screen data: Application to the Japanese Trial-Ready Cohort study.
Article in Alzheimer's & dementia (New York, N. Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed.
- Prediction of one-year cognitive decline via self-perceived memory in older adults during the COVID-19 pandemic.JAR life · 2026Article
- 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
- Factors affecting participation in web-based Alzheimer's questionnaire surveys: Lessons from the Japanese trial-ready cohort.JAR life · 2025Article
- Artificial intelligence for optimizing recruitment and retention in clinical trials: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Public perceptions related to healthcare preparedness to anti-amyloid therapies for Alzheimer's Disease in Japan.Alzheimer's research & therapy · 2024Observational
- Combining plasma Aβ and p-tau217 improves detection of brain amyloid in non-demented elderly.Alzheimer's research & therapy · 2024Article
- Predicting positron emission tomography brain amyloid positivity using interpretable machine learning models with wearable sensor data and lifestyle factors.Alzheimer's research & therapy · 2023Observational
- Predicting amyloid-beta pathology in the general population.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023Article
- Molecular Pathogenesis and Disease-modifying Therapies of Alzheimer's Disease and Related Disorders.JMA journal · 2022Review
- Automated Evaluation of Conventional Clock-Drawing Test Using Deep Neural Network: Potential as a Mass Screening Tool to Detect Individuals With Cognitive Decline.Frontiers in neurology · 2022Article
- Efficacy and Cost-effectiveness of Promotion Methods to Recruit Participants to an Online Screening Registry for Alzheimer Disease Prevention Trials: Observational Study.Journal of medical Internet research · 2021Observational
- Predicting amyloid risk by machine learning algorithms based on the A4 screen data: Application to the Japanese Trial-Ready Cohort study.Alzheimer's & dementia (New York, N. Y.) · 2021Article
- Editorial: Alzheimer's Disease Research in Japan: A Short History, Current Status and Future Perspectives toward Prevention.The journal of prevention of Alzheimer's disease · 2021Article
- Cohort-Specific Optimization of Models Predicting Preclinical Alzheimer's Disease, to Enhance Screening Performance in the Middle of Preclinical Alzheimer's Disease Clinical Studies.The journal of prevention of Alzheimer's disease · 2021Article
- The Worldwide Alzheimer's Disease Neuroimaging Initiative: ADNI-3 updates and global perspectives.Alzheimer's & dementia (New York, N. Y.) · 2021Article
- Computerized cognitive practice effects in relation to amyloid and tau in preclinical Alzheimer's disease: Results from a multi-site cohort.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Characterizing Japanese older adults without dementia by amyloid PET status: A comparative study of amyloid-positive and amyloid-negative groups from Japanese trial-ready cohort study.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Blood-based biomarker prescreening with different testing combinations and cutoffs: A simulation study examining efficacy and cost-effectiveness in Alzheimer's disease prevention studies.Alzheimer's & dementia (New York, N. Y.)Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundSelecting cognitively normal elderly individuals with higher risk of brain amyloid deposition is critical to the success of prevention trials for Alzheimer's disease (AD).
methodsBased on the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease study data, we built machine-learning models and applied them to our ongoing Japanese Trial-Ready Cohort (J-TRC) webstudy participants registered within the first 9 months (
resultsAge, family history, online Cognitive Function Instrument and CogState scores were important predictors. In a subgroup of J-TRC webstudy participants with known amyloid status ( DISCUSSION: Our algorithms may be usable for automatic prioritization of candidate participants with higher amyloid risks to be preferentially recruited from the J-TRC webstudy to in-person study, maximizing efficiency for the identification of preclinical AD participants.
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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.