AI agent classifies genetic disease severity at 93.55% accuracy
An agent graded 10,211 HPO terms at 93.55% accuracy on expert cohorts, but the first-party result awaits independent replication.
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You can now grade 10,211 Human Phenotype Ontology terms by severity with an agent combining ReAct and retrieval-augmented generation, reaching 93.55% accuracy (MCC 0.9237) on expert-curated cohorts.
Previously, severity grading relied on manual literature and guideline review, which was costly and hard to scale across all terms; this system retrieves PubMed literature against ACMG severity guidelines and ACOG quality-of-life criteria and generates checkable reasoning chains. The authors state 82.6% to 91.4% of claims were supported by direct evidence or valid inference, and gene-level concordance with the Mackenzie's Mission gene list was 95.2%.
The result is reported first-party by the research team on the authors' own curated cohorts; clinical or panel-design use remains unverified, with no independent replication. It appears in an arXiv preprint.