Fig. 7

Deep neural network optimized with genetic algorithm performed excellently in predicting TMB of gastrointestinal cancers. A Structure of the deep neural network (DNN) with one input layer of 10 features after PCA, two hidden layers of 57 and 17 neurons, one output layer of TMB. B Flowchart of genetic algorithm during DNN optimization. C Record of optimization after evolution of 30 generations. Fitness referring to Pearson relevance coefficient, r, between actual value and predicted value in validation set. D Bar plot of TMB showing ability of the DNN model to fit the fluctuation of the data. Bars in blue and orange refer to actual values and predicted values, respectively. E Assessment of DNN model with Pearson relevance analysis in three datasets. Black circles, blue squares and red triangles stand for samples in training set, validation set and testing set, with relevance coefficient of 0.98, 0.82 and 0.92, respectively