AI model predicts chronic rhinosinusitis using nationwide EHR data

Researchers have developed a new method to predict chronic rhinosinusitis (CRS) using nationwide electronic health record (EHR) data. The approach leverages two years of pre-diagnostic history and a hybrid feature-selection pipeline to distill over 110,000 potential codes into 100 interpretable features. By training demographic-stratified models across six subgroups, the framework achieved an AUC of 0.8461, demonstrating improved discrimination for risk stratification and potential for earlier triage in primary care. AI

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IMPACT Demonstrates the potential of EHR data for disease risk stratification, potentially improving patient triage and care.

RANK_REASON This is a research paper published on arXiv detailing a new predictive model. [lever_c_demoted from research: ic=1 ai=0.4]

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• Chronic Rhinosinusitis
• All of Us Research Program
• EHR

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