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Table 1 The pseudocode

From: Predicting miRNA-disease associations via layer attention graph convolutional network model

Input:

miRNA–miRNA similarities matrix, disease–disease similarities matrix, adjacent matrix A;

Construct the input graph G = (V,E)

Output:

Initialize embedded dimension, learning rate, training epoch, dropout rates;

Initialize embeddings;

Iterate according to the layerwise propagation rule of GCN;

Introduce an attention mechanism;

Combine other embeddings and obtain final embeddings of miRNAs and diseases;

Obtain the Loss function