New CRC miRNA

April 11, 2022
Machine-Learning-Based Analysis Identifies miRNA Expression Profile for Diagnosis and Prediction of Colorectal Cancer.
We developed a predictive model with 19 cases through the Azure ML platform. First, we tested a model using various algorithms, such as Two-class Decision Forest, Two-class Decision Jungle, Two-class Bayes Point Machine, Two-class Support Vector Machine, and Two-class Neural Network. Two-class Bayes Point Machine showed the best accuracy and precision, which were respectively 0.947 and 0.917 (Figure 2). The AUC of the ROC curve was 0.955. The threshold has been set to the optimum cut-off value of 0.4.