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DMoVGPE model architecture diagram. Figure a. illustrates the overall architecture of the DMoVGPE model. A gating network, implemented as a neural network with a softmax activation function, assigns probabilities to multiple VGPR experts based on the input microbial data. Each expert is specialized for a specific disease state, such as Disease I, Disease II, Disease III, or Control. The gating network dynamically weights the predictions from these experts, enabling a weighted aggregation of their outputs for each input. This dynamic weighting mechanism ensures the model adapts to the input features, tailoring the prediction to disease-specific patterns.

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