Role of Artificial Intelligence in Hepatitis B Virus-Associated Liver Injury Diagnosis Relationship - Sharma, Kanisheka; Alam, Inkashaf; Sawhney, Shagun; datta, Surbhi; Azmi, Asmat; Kapoor, Deepika; Jayaswal, R P; Shweta, Shweta; Kumar, Barjesh (Journal of Neonatal Surgery, 2025)
ABSTRACT HBV infection is one of the most significant health problems worldwide and the most frequent causes of chronic liver disease, cirrhosis and hepatocellular carcinoma. The mechanism of liver injury in HBV infection is a complicated process that is catalyzed by the viral replication, host immune response and progressive fibrotic alteration. Knowledge of the HBV life cycle since the entry of the hepatocytes and covalently closed circulation DNA to viral replication and maintenance is crucial to correlate molecular pathogenesis of HBV with clinical liver damage. The traditional methods of diagnosis, such as serological markers, biochemical parameters and image procedures such as ultrasonography, computed tomography are important in evaluation of the disease. Artificial intelligence (AI) has recently become the hepatological power tool that helps to improve the accuracy of non-invasive imaging based and assessing liver fibrosis, inflammation and early hepatocellular carcinoma. Machine learning and deep learning algorithm make it possible to interpret images automatically, predict risk and disease progression. This review focuses on the interrelation between HBV viral pathogenesis and liver injury pathogenesis and the rising presence of AI-based diagnostic, monitoring and clinical decision-making in HBV related liver disease. ..