ArticleAlzheimer's research & therapy2022
ADataViewer: exploring semantically harmonized Alzheimer's disease cohort datasets.
Article in Alzheimer's research & therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed.
- Encoding Discordance in the Alzheimer's Disease A/T/N Framework.medRxiv : the preprint server for health sciences · 2026Article
- Evaluating language model embeddings for Parkinson's disease cohort harmonization using a novel manually curated variable mapping schema.Scientific reports · 2025Article
- Semantic search helper: A tool based on the use of embeddings in multi-item questionnaires as a harmonization opportunity for merging large datasets - A feasibility study.European psychiatry : the journal of the Association of European Psychiatrists · 2025Article
- A natural language processing approach to support biomedical data harmonization: Leveraging large language models.PloS one · 2025Article
- psHarmonize: Facilitating reproducible large-scale pre-statistical data harmonization and documentation in R.Patterns (New York, N.Y.) · 2024Article
- Data-Driven Thresholding Statistically Biases ATN Profiling across Cohort Datasets.The journal of prevention of Alzheimer's disease · 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
- Semantic Harmonization of Alzheimer's Disease Datasets Using AD-Mapper.Journal of Alzheimer's disease : JAD · 2024Article
- Current state of data stewardship tools in life science.Frontiers in big data · 2024Review
- Deep learning-based patient stratification for prognostic enrichment of clinical dementia trials.Brain communications · 2024Article
- An ontology-based approach for harmonization and cross-cohort query of Alzheimer's disease data resources.BMC medical informatics and decision making · 2023Article
- Comparison and aggregation of event sequences across ten cohorts to describe the consensus biomarker evolution in Alzheimer's disease.Alzheimer's research & therapy · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundCurrently, Alzheimer's disease (AD) cohort datasets are difficult to find and lack across-cohort interoperability, and the actual content of publicly available datasets often only becomes clear to third-party researchers once data access has been granted. These aspects severely hinder the advancement of AD research through emerging data-driven approaches such as machine learning and artificial intelligence and bias current data-driven findings towards the few commonly used, well-explored AD cohorts. To achieve robust and generalizable results, validation across multiple datasets is crucial.
methodsWe accessed and systematically investigated the content of 20 major AD cohort datasets at the data level. Both, a medical professional and a data specialist, manually curated and semantically harmonized the acquired datasets. Finally, we developed a platform that displays vital information about the available datasets.
resultsHere, we present ADataViewer, an interactive platform that facilitates the exploration of 20 cohort datasets with respect to longitudinal follow-up, demographics, ethnoracial diversity, measured modalities, and statistical properties of individual variables. It allows researchers to quickly identify AD cohorts that meet user-specified requirements for discovery and validation studies regarding available variables, sample sizes, and longitudinal follow-up. Additionally, we publish the underlying variable mapping catalog that harmonizes 1196 unique variables across the 20 cohorts and paves the way for interoperable AD datasets.
conclusionsIn conclusion, ADataViewer facilitates fast, robust data-driven research by transparently displaying cohort dataset content and supporting researchers in selecting datasets that are suited for their envisioned study. The platform is available at https://adata.scai.fraunhofer.de/ .
Indexed as
Identifiers
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.