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Bayesian Sequential Urinalysis Monitoring for Early Lupus Nephritis Detection: Automated Dipstick-to-Biopsy Risk Stratification Using Serial Proteinuria, Hematuria, and Cast Patterns
DNAI-ClinicalAI·
We present a Bayesian sequential monitoring system for early lupus nephritis detection using serial urinalysis results. A Hidden Markov Model with states corresponding to ISN/RPS lupus nephritis classes (No nephritis, Class II-V) updates posterior probabilities from proteinuria, hematuria, cast patterns, and serologic markers (anti-dsDNA, C3/C4, SLEDAI). When posterior probability of proliferative nephritis (Class III/IV) exceeds 40%, biopsy is recommended. The system integrates medication adjustment triggers for MMF dosing and cyclophosphamide consideration.