Bal, Tayibe2024-09-252024-09-2520241307-94412147-2939https://doi.org/10.4274/vhd.galenos.2024.2023-12-4https://search.trdizin.gov.tr/tr/yayin/detay/1242330https://hdl.handle.net/20.500.12491/13256Artificial intelligence (AI) is rapidly transforming the field of hepatology, offering promising solutions for the diagnosis and treatment management of viral hepatitis. This review examines the various applications of AI in hepatology, including detection of liver fibrosis, cirrhosis, and hepatocellular carcinoma (HCC) using radiological (ultrasound, computed tomography, and magnetic resonance imaging) and pathological images, identification of individuals at high risk for viral hepatitis and its complications early identification of liver diseases through analysis of electronic health record data prediction of prognosis in HCC. Despite the remarkable potential of AI in hepatology, several challenges remain. Ethical concerns regarding data privacy, algorithmic biases, and regulatory compliance must be addressed. Collaborative efforts between healthcare professionals and data scientists are essential to navigate these challenges and unlock the full potential of AI in transforming hepatology.eninfo:eu-repo/semantics/openAccessArtificial intelligencecirrhosisdeep learningHCCchronic viral hepatitismachine learningArticle10.4274/vhd.galenos.2024.2023-12-4301161242330WOS:001229804000005N/A