Machine learning-based clinical decision support system for treatment recommendation and overall survival prediction of hepatocellular carcinoma: a multi-center study
We proposed a machine learning-based clinical decision support system with 20 clinical variables. The model consists of two stages: the first stage recommends initial treatment using an ensemble voting machine, and the second stage predicts post-treatment survival using a random survival forest algorithm.
