Abstract
Hepatitis B virus infection remains a significant global health challenge, particularly in endemic regions like Vietnam. This article examines the groundbreaking study by Nguyen et al, which investigates the relationship between human leukocyte antigen-DP/DQ polymorphisms and hepatitis B virus-related liver disease progression. Through advanced multi-clustering analysis, the study reveals that the A-A-A haplotype (rs2856718-rs3077-rs9277535) provides protection against disease progression, while the G-G-G haplotype correlates with increased hepatocellular carcinoma susceptibility. The integration of machine learning approaches with genetic data offers promising avenues for refined disease prediction and personalized therapeutic strategies. This article discusses the implications for expanding study populations, implementing longitudinal cohort studies, and leveraging artificial intelligence for improved patient outcomes.