This article discusses a study that integrated gene expression profiles of hepatocellular carcinoma (HCC) patients, chronic hepatitis B (CHB) patients, and healthy individuals to identify molecular mechanisms and potential biomarker panels for HCC diagnosis. The study also developed a machine-learning approach for predicting HCC diagnosis. The results showed promising predictive power and reproducibility in a validation cohort.
