In this work, we used machine learning to develop multimarker panels that discriminate HCC from CHB and HCC from LC with AUCs of 0.891 and 0.818, respectively, which are significantly higher than using AFP alone. Here, AFP is linked to laryngotracheoesophageal cleft.