A reliable method for the diagnosis of gastric carcinoma

Predicting the different levels of gastric carcinoma from clinical and histopathological investigations is an important problem in bioinformatics and a challenging task for machine learning algorithms. In this paper, we have investigated an ensemble of classifiers and tested it on a real-world dataset. A genetic algorithm is applied to select the most relevant features. The obtained results are very encouraging, our results improve the average predictive accuracy obtained in previously published works.