Figure 1-.

Algorithm specifications for Deep Neural Network (DNN) used in Model 1. All variables underwent processing through a 7 layer artificial neural network with above specified neurons in each layer. Images were analyzed in groups of 4 at a time until all 18 were completed, at which point the algorithm would adjust predictive variable weights and repeat for 25 epochs/repeats. Upon completion, the final algorithm would be used to verify accuracy on 10 unseen images from the original dataset. Images were redistributed randomly into test/training groups, model weights were reinitialized and randomized and the entire process was repeated 200 times for population data collection.