Hepatocellular Carcinoma Detection Using Machine Learning Techniques.

Hepatocellular carcinoma (HCC) is a form of primary cancer appearing in the liver. In this work used the hepatocellular carcinoma dataset from the UCI machine learning repository and tested different techniques for feature selection and classification. The following algorithms were used: decision trees, random forests, SVMs, k-NN classifiers, AdaBoost, and gradient boost. The best results were obtained using gradient boost with 84% accuracy and 93% precision. Finally, we deployed the model to a web application as a decision support system for clinicians.