ArticleAlzheimer disease and associated disorders
Global Data Sharing in Alzheimer Disease Research.
Article in Alzheimer disease and associated disorders. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data.Frontiers in aging neuroscience · 2019Pooled it
- Global Diseases Deserve Global Solutions: Alzheimer's Disease.Neurology international · 2025Review
- Unraveling the Mysteries of Alzheimer's Disease Using Artificial Intelligence.Reviews on recent clinical trials · 2025Review
- An ontology-based approach for modelling and querying Alzheimer's disease data.BMC medical informatics and decision making · 2023Article
- DementiaBank: Theoretical Rationale, Protocol, and Illustrative Analyses.American journal of speech-language pathology · 2023Article
- Data Archive for the BRAIN Initiative (DABI).Scientific data · 2023Article
- Data sharing in neurodegenerative disease research: challenges and learnings from the innovative medicines initiative public-private partnership model.Frontiers in neurology · 2023Review
- Clinical Data Interchange Standards in Clinical Trials on Alzheimer's Disease.Psychiatry investigation · 2022Article
- Applications of Phyto-Nanotechnology for the Treatment of Neurodegenerative Disorders.Materials (Basel, Switzerland) · 2022Review
- 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
- On Improved 3D-CNN-Based Binary and Multiclass Classification of Alzheimer's Disease Using Neuroimaging Modalities and Data Augmentation Methods.Journal of healthcare engineering · 2022Article
- Artificial Intelligence for Alzheimer's Disease: Promise or Challenge?Diagnostics (Basel, Switzerland) · 2021Review
- Using Digital Tools to Advance Alzheimer's Drug Trials During a Pandemic: The EU/US CTAD Task Force.The journal of prevention of Alzheimer's disease · 2021Article
- The Application of Artificial Intelligence in the Genetic Study of Alzheimer's Disease.Aging and disease · 2020Review
- National Neuroinformatics Framework for Canadian Consortium on Neurodegeneration in Aging (CCNA).Frontiers in neuroinformatics · 2018Article
- Accelerating drug development for Alzheimer's disease through the use of data standards.Alzheimer's & dementia (New York, N. Y.) · 2017Article
- Publishing descriptions of non-public clinical datasets: proposed guidance for researchers, repositories, editors and funding organisations.Research integrity and peer review · 2016Article
- Big biomedical data as the key resource for discovery science.Journal of the American Medical Informatics Association : JAMIA · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Many investigators recognize the importance of data sharing; however, they lack the capability to share data. Research efforts could be vastly expanded if Alzheimer disease data from around the world was linked by a global infrastructure that would enable scientists to access and utilize a secure network of data with thousands of study participants at risk for or already suffering from the disease. We discuss the benefits of data sharing, impediments today, and solutions to achieving this on a global scale. We introduce the Global Alzheimer's Association Interactive Network (GAAIN), a novel approach to create a global network of Alzheimer disease data, researchers, analytical tools, and computational resources to better our understanding of this debilitating condition. GAAIN has addressed the key impediments to Alzheimer disease data sharing with its model and approach. It presents practical, promising, yet, data owner-sensitive data-sharing solutions.
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What OpenQuestion holds
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.