Figure 4.

Structure and performance of our best machine learning based model in predicting high and low risk severity score evaluated by confusion matrix and AUC of ROC. The best machine learning model with the highest performance is a deep neural network model with 12 neurons in the input layer including age, total cholesterol, triglyceride, low-density lipoprotein (LDL), high-density lipoprotein (HDL), systolic blood pressure, HbA1c, glucose, sex and Id3SNP after all these inputs were normalized and transformed. The model contained 12 and 6 neurons in the next sequential layers and an output layer (A). The model performance was evaluated on 82 patients in the testing set. With our best model, the low risk group was predicted NPV of 81% and high risk group with PPV of 87% (B). ROC plot showing the performance of the model (blue line) with an AUC of 0.84 and random (dashed red line) for comparison (C).