Machine learning-based gray-level co-occurrence matrix signature for predicting lymph node metastasis in undifferentiated-type early gastric cancer

Figure 4 Visualization of prediction models based on artificial neural network algorithm. A: Artificial neural network model; B: Importance of variables using connection weights. Candidate factors associated with lymph node metastasis are ordered via artificial neural network (ANN) algorithm and prediction nodes, and weights are assigned via an ANN algorithm. IV_0: Inertia value 0°; IV_45: Inertia value 45°; IG_0: Inverse gap 0°; IG_45: Inverse gap 45°; IG_all: Inverse gap full angle; Haralick_30: Haralick 30°; Haralick_all: Haralick full angle.