Detection of Colorectal Carcinoma Based on Microbiota Analysis Using Generalized Regression Neural Networks and Nonlinear Feature Selection

To obtain a screening tool for colorectal cancer (CRC) based on gut microbiota, we seek here to identify an optimal classifier for CRC detection as well as a novel nonlinear feature selection method for determining the most discriminative microbial species. In this study, the intestinal microflora in feces of 141 patients were modeled using general regression neural networks (GRNNs) combined with the proposed feature selection method. The proposed model led to slightly higher accuracy {\mathrm{(AUC}}= {\mathrm{0.911}}) ( AUC =0.911) than previous studies {\mathrm{(AUC}}< {\mathrm{0.87}}) ( AUC