Model
DISEASE
The samples were randomly divided into a training set and a validation set at a ratio of 7∶3 for the establishment and validation of the model, respectively. Five machine learning algorithms including SVM, MLP, DT, RFC, and AdaBoost were used to establish the prediction model. SVM solves the binary classification problem by fitting a maximum margin discriminator to a dataset in a kernel-induced feature space, and it has been applied in many medical diagnostics and disease classifications [