ArticleJournal of Alzheimer's disease : JAD2024
Semantic Harmonization of Alzheimer's Disease Datasets Using AD-Mapper.
Article in Journal of Alzheimer's disease : JAD, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Encoding Discordance in the Alzheimer's Disease A/T/N Framework.medRxiv : the preprint server for health sciences · 2026Article
- A benchmark of text embedding models for semantic harmonization of Alzheimer's disease cohorts.The journal of prevention of Alzheimer's disease · 2025Article
- Evaluating language model embeddings for Parkinson's disease cohort harmonization using a novel manually curated variable mapping schema.Scientific reports · 2025Article
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Authors and funding
13 authors.
Funding
Abstract
Background: Despite numerous past endeavors for the semantic harmonization of Alzheimer's disease (AD) cohort studies, an automatic tool has yet to be developed. Objective: As cohort studies form the basis of data-driven analysis, harmonizing them is crucial for cross-cohort analysis. We aimed to accelerate this task by constructing an automatic harmonization tool. Methods: We created a common data model (CDM) through cross-mapping data from 20 cohorts, three CDMs, and ontology terms, which was then used to fine-tune a BioBERT model. Finally, we evaluated the model using three previously unseen cohorts and compared its performance to a string-matching baseline model. Results: Here, we present our AD-Mapper interface for automatic harmonization of AD cohort studies, which outperformed a string-matching baseline on previously unseen cohort studies. We showcase our CDM comprising 1218 unique variables. Conclusion: AD-Mapper leverages semantic similarities in naming conventions across cohorts to improve mapping performance.
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