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.
gastric carcinoma ensemble of classifiers feature selection