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Demonstrates machine learning predicts chronic rhinosinusitis in health record cohorts, indicating real-world application benefits.
KEY POINTS: Machine learning identifies reproducible pre-diagnostic CRS trajectories in large EHR cohorts. Models show stable external performance (AUC ∼ 0.81), supporting real-world generalizability. Predictors highlight evolving CRS workups and models may serve as future decision support tools.
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Varghese et al. (2026) studied this question.
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