Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma

Figure 2 Flow diagram for the radiomics of machine learning. A: Construct radiomics models, the volume of interest was delineated by experienced radiologists and three-dimensional images were formed, extracting quantitative features by software; B: Pathologic examination, firstly obtaining specimens of small hepatocellular carcinoma tissue, and then taking pathologic diagnosis for microvascular invasion; C: Data cleaning and dimensions reduction; D: Establishing the model for predicting microvascular invasion by machine learning. LR: Logistic regression; KNN: K-Nearest neighbor; SVM: Support vector machine; RF: Random forest.