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Improving Liver Fibrosis Diagnosis in Primary Care Using FibroX AI

Yale University · 2026
ClinicalTrials.gov · Datasets · License: Public Domain · 2026
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The goal of this clinical trial is to learn whether an artificial intelligence (AI) tool called FibroX can help primary care providers better diagnose significant liver fibrosis (≥F2) and clinically significant portal hypertension in adults with metabolic dysfunction-associated steatotic liver disease (MASLD). The main questions it aims to answer are: * Can FibroX improve the accuracy of diagnosing significant liver fibrosis (≥F2) and clinically significant portal hypertension compared to usual care? * Is FibroX easy to use and acceptable to primary care providers in simulated clinical settings? * Do providers trust FibroX as a decision-support tool? Researchers will compare FibroX-assisted care to usual care to see if FibroX improves diagnostic accuracy, provider trust, and supports better decision-making. Participants will: * Be primary care providers (MDs, DOs, NPs, PAs) from diverse clinics * Review simulated patient cases with MASLD risk factors * Use either usual care tools (standard labs and optional FIB-4 calculator) or FibroX (AI-generated risk score, triage band, and explainability panel) * Make diagnostic and referral decisions for each case * Complete surveys on usability, trust in AI, confidence, and cognitive workload This study will help determine whether FibroX can be integrated into real-world primary care workflows to support earlier and more accurate detection of liver fibrosis and portal hypertension, potentially reducing missed diagnoses, unnecessary referrals, and improving patient outcomes.
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