Clinical Trial: AI Models vs Non-Invasive Fibrosis Scores in MAFLD Diagnosis
Study Status: COMPLETED
Recruit Status: COMPLETED
Condition: MAFLD
Study Type: OBSERVATIONAL
Official Title: Assessing the Utility of AI Models in MAFLD Diagnosis: Comparison With Traditional Non-Invasive Fibrosis Scores.
Brief Summary:
This study evaluates the accuracy of artificial intelligence (AI) models using FibroScan and clinical data to predict hepatic fibrosis in Egyptian patients with metabolic-associated fatty liver disease (MAFLD).The performance of the AI models will be compared with conventional noninvasive fibrosis scores (FIB-4, APRI, NAFLD fibrosis score, and FAST).The goal is to improve early, noninvasive diagnosis of fibrosis and reduce reliance on liver biopsy.
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