The article discusses the development of a machine learning algorithm aimed at improving the accuracy of hepatocellular carcinoma (HCC) prediction in patients with chronic hepatitis B who are undergoing antiviral therapy. The study provides baseline characteristics of the population, including variables such as age, gender, height, weight, and various medical indicators.
The article also identifies independent predictors of HCC development and compares the machine learning-based risk prediction model with other existing models. The machine learning model demonstrated a high area under the curve (AUC) value, indicating its potential effectiveness in predicting HCC risk.