ArticleScientific reports2021
Using imputation to provide harmonized longitudinal measures of cognition across AIBL and ADNI.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 31 citations in OpenAlex.
- Data‑driven cognitive composites predict Aβ‑related decline and progression to MCI: the ADOPIC study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Bridging the Gap: Missing Data Imputation Methods and Their Effect on Dementia Classification Performance.Brain sciences · 2025Article
- Flexible imputation toolkit for electronic health records.Scientific reports · 2025Article
- c-Triadem: A constrained, explainable deep learning model to identify novel biomarkers in Alzheimer's disease.PloS one · 2025Article
- Overview of Alzheimer's Disease Neuroimaging Initiative and future clinical trials.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Alzheimer's Disease Neuroimaging Initiative: Two decades of pioneering Alzheimer's disease research and future directions.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- LD-informed deep learning for Alzheimer's gene loci detection using WGS data.medRxiv : the preprint server for health sciences · 2024Article
- Understanding machine learning applications in dementia research and clinical practice: a review for biomedical scientists and clinicians.Alzheimer's research & therapy · 2024Review
- ReMiND: Recovery of missing neuroimaging using diffusion models with application to Alzheimer's disease.Imaging neuroscience (Cambridge, Mass.) · 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
- Association of Chronic Pain with Biomarkers of Neurodegeneration, Microglial Activation, and Inflammation in Cerebrospinal Fluid and Impaired Cognitive Function.Annals of neurology · 2023Article
- Applications of generative adversarial networks in neuroimaging and clinical neuroscience.NeuroImage · 2023Review
- Harmonizing Ethno-Regionally Diverse Datasets to Advance the Global Epidemiology of Dementia.Clinics in geriatric medicine · 2023Review
- Understanding ethnic diversity in open dementia neuroimaging data sets.Brain communications · 2023Article
- Chronic neuropsychiatric sequelae of SARS-CoV-2: Protocol and methods from the Alzheimer's Association Global Consortium.Alzheimer's & dementia (New York, N. Y.) · 2022Article
- Article
- Machine learning based multi-modal prediction of future decline toward Alzheimer's disease: An empirical study.PloS one · 2022Article
- A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias.Frontiers in neuroimaging · 2022Article
- LD-informed deep learning for Alzheimer's gene loci detection using WGS data.Alzheimer's & dementia (New York, N. Y.)Article
- A robust harmonization approach for cognitive data from multiple aging and dementia cohorts.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
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Authors and funding
18 authors at 8 institutions in 2 countries.
Funding
Abstract
To improve understanding of Alzheimer's disease, large observational studies are needed to increase power for more nuanced analyses. Combining data across existing observational studies represents one solution. However, the disparity of such datasets makes this a non-trivial task. Here, a machine learning approach was applied to impute longitudinal neuropsychological test scores across two observational studies, namely the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) providing an overall harmonised dataset. MissForest, a machine learning algorithm, capitalises on the underlying structure and relationships of data to impute test scores not measured in one study aligning it to the other study. Results demonstrated that simulated missing values from one dataset could be accurately imputed, and that imputation of actual missing data in one dataset showed comparable discrimination (p < 0.001) for clinical classification to measured data in the other dataset. Further, the increased power of the overall harmonised dataset was demonstrated by observing a significant association between CVLT-II test scores (imputed for ADNI) with PET Amyloid-β in MCI APOE-ε4 homozygotes in the imputed data (N = 65) but not for the original AIBL dataset (N = 11). These results suggest that MissForest can provide a practical solution for data harmonization using imputation across studies to improve power for more nuanced analyses.
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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.