ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2023
Early prediction of Alzheimer's disease and related dementias using real-world electronic health records.
Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 2 of them syntheses that pooled it.
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Who cites it
63 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Electronic health record-based prediction models for dementia detection: a systematic review of model performance and quality.Journal of the American Medical Informatics Association : JAMIA · 2026Pooled it
- Machine learning based algorithms for virtual early detection and screening of neurodegenerative and neurocognitive disorders: a systematic-review.Frontiers in neurology · 2024Pooled it
- Identifying sex-specific sub-phenotypes of Alzheimer's disease progression using longitudinal electronic health records.EBioMedicine · 2026Article
- Predicting future dementia from routine clinical MRI and linked healthcare data.Alzheimer's research & therapy · 2026Article
- A dynamic risk prediction framework for Alzheimer's disease and related dementias with interpretability.NPJ digital medicine · 2026Article
- Integrative machine learning approach to risk prediction for dementia and Alzheimer's disease.GeroScience · 2026Article
- Leveraging electronic health records to examine differential clinical outcomes in people with Alzheimer's disease.Communications medicine · 2026Article
- Young Adult Substance Use as a Predictor of Poor Self-Rated Memory Decades Later in Midlife.Journal of aging and health · 2026Article
- Bloodwork-free Early Screening for Alzheimer's Disease via Comorbid Pattern Recognition in Electronic Health Records.Research square · 2026Article
- Review of Artificial Intelligence for Clinical Use in Alzheimer's Disease and Related Dementias.Seminars in neurology · 2026Review
- The Use of Artificial Intelligence in Improving Diagnostic Modalities in Rheumatoid Arthritis: A Narrative Review.Cureus · 2026Review
- A retrieval-augmented generation large language model framework for accurate dementia identification from electronic health records.medRxiv : the preprint server for health sciences · 2026Article
- Early prediction of Alzheimer's disease using longitudinal electronic health records of US military veterans.Communications medicine · 2026Article
- The Role of Microglial Cells and Cytokine Modulation in Alzheimer's Disease: A Neuroinflammatory Perspective.Current Alzheimer research · 2026Review
- Acoustic Analysis of Primary Care Patient-provider Conversations to Screen for Cognitive Impairment.medRxiv : the preprint server for health sciences · 2025Article
- Fair positive unlabeled learning for predicting undiagnosed Alzheimer's disease in diverse electronic health records.NPJ digital medicine · 2025Article
- Predictive factors for dementia among older adults in South Korea: an interpretable machine learning analysis.Alzheimer's research & therapy · 2025Article
- Predicting Alzheimer's Disease Diagnosis, a Decade or more Years before Onset using the Electronic Health Record and Random Forest Machine Learning Models.medRxiv : the preprint server for health sciences · 2025Article
- A Self-Explainable Dynamic Risk Monitoring Framework for Predicting Alzheimer's Disease and Related Dementias.medRxiv : the preprint server for health sciences · 2025Article
- Identifying clinical feature clusters toward predicting stroke in patients with asymptomatic carotid stenosis.International journal of data science and analytics · 2025Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
introductionThis study aims to explore machine learning (ML) methods for early prediction of Alzheimer's disease (AD) and related dementias (ADRD) using the real-world electronic health records (EHRs).
methodsA total of 23,835 ADRD and 1,038,643 control patients were identified from the OneFlorida+ Research Consortium. Two ML methods were used to develop the prediction models. Both knowledge-driven and data-driven approaches were explored. Four computable phenotyping algorithms were tested.
resultsThe gradient boosting tree (GBT) models trained with the data-driven approach achieved the best area under the curve (AUC) scores of 0.939, 0.906, 0.884, and 0.854 for early prediction of ADRD 0, 1, 3, or 5 years before diagnosis, respectively. A number of important clinical and sociodemographic factors were identified. DISCUSSION: We tested various settings and showed the predictive ability of using ML approaches for early prediction of ADRD with EHRs. The models can help identify high-risk individuals for early informed preventive or prognostic clinical decisions.
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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.