ArticleStudies in health technology and informatics2025
Identifying Phenotypes for Earlier Diagnosis of Rare Diseases.
Article in Studies in health technology and informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- The European Health Data Space and biobanking in Europe: synergies, tensions and the future governance of data-driven health research.Frontiers in genetics · 2026Review
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Authors and funding
3 authors.
Funding
Abstract
Rare diseases, while individually rare, cumulatively affect a large population, and patients often undergo long and arduous diagnostic odysseys. Toward the goal of supporting earlier diagnosis of rare diseases, we developed generalizable methods of extracting rare diseases and phenotypes from structured electronic health records and clinical notes. We analyzed the distributions of the age of onset of phenotypes per disease to identify disease-phenotype associations, producing a dataset with over 500 thousand associations covering 2300 rare diseases. Disease-phenotype associations are characterized by disease prevalence and mean age of onset of the phenotype to aid phenotype selection according to the priorities of the clinical decision support task.
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Registered trials
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