ArticleAmerican journal of human genetics2025
First steps toward building natural history of diseases computationally: Lessons learned from the Noonan syndrome use case.
Article in American journal of human genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- OntoCodex: a multi-agent biomedical ontology enrichment framework.npj health systems · 2026Article
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6 authors.
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Abstract
Rare diseases (RDs) are conditions affecting fewer than 1 in 2,000 people, with over 7,000 identified, primarily genetic in nature, and more than half impacting children. Although each RD affects a small population, collectively, between 3.5% and 5.9% of the global population, or 262.9-446.2 million people, live with an RD. Most RDs lack established treatment protocols, highlighting the need for proper care pathways addressing prognosis, diagnosis, and management. Advances in generative AI and large language models (LLMs) offer new opportunities to document the temporal progression of phenotypic features, addressing gaps in current knowledge bases. This study proposes an LLM-based framework to capture the natural history of diseases, specifically focusing on Noonan syndrome. The framework aims to document phenotypic trajectories, validate against RD knowledge bases, and integrate insights into care coordination using electronic health record (EHR) data from the Undiagnosed Diseases Program Singapore.
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