I am using a neural network with two output neurons for my omics data to predict the binary classification of genes. It is important in the study to know the feature importance. I know that the Garson's algorithm and connection weights algorithm are used in neural networks with one hidden layer, but in all the examples I've seen there is only one output neuron. My neural network has two output neurons. Can I still use these algorithms to evaluate feature importance in my neural network?