  We exploit liver cancer prediction model using machine learning algorithms
based on epidemiological data of over 55 thousand peoples from 2014 to the
present. The best performance is an AUC of 0.71. We analyzed model parameters
to investigate critical risk factors that contribute the most to prediction.
