Diagnostic accuracy of artificial intelligence models for imaging detection of hepatic steatosis through systematic review and meta analysis.

ABSTRACT: Non-alcoholic fatty liver disease (NAFLD) is an increasingly prevalent chronic liver condition affecting nearly 30% of the global population. Characterized by hepatic steatosis in the absence of significant alcohol intake, NAFLD can progress to non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and hepatocellular carcinoma. Although liver biopsy is the diagnostic gold standard, its invasiveness, cost, and associated risks limit widespread application. Artificial intelligence (AI) offers promising non-invasive alternatives by leveraging large datasets to enhance diagnostic precision. To evaluate the diagnostic accuracy of artificialintelligence algorithms for the imaging detection of hepatic steatosis, the essential first step in the metabolic dysfunctionassociated steatotic liver d

SUBMITTER: Nivethitha V 

PROVIDER: S-EPMC12491402 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature