Machine learning prediction model for gray-level co-occurrence matrix features of synchronous liver metastasis in colorectal cancer

Figure 5 Construction of pulmonary infection prediction model via artificial neural network model. A: The formula of artificial neural network model is as follows: θ = θ-η × ∇ (θ).J (θ). Among them “η” is the learning rate, “so (θ).J (θ)” represents the gradient change of the loss function [i.e., J(θ)]; B: Variable importance using connection weights for the artificial neural network model. IND: Inverse difference; SUV: Sum variance; SUE: Sum entropy; DIV: Difference variance; SOS: Sum of squares; MES: Mean sum.