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Table 2 Performance of model training without gene weight layer in different r-radius

From: SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures

Features r-radius MSE \(R^2\)
Gene expression 1 1.0765 0.8489
2 0.9727 0.8634
3 1.0763 0.8489
Gene expression + genetic mutation 1 1.0663 0.8503
2 0.9853 0.8616
3 1.1061 0.8447
  1. Bold values represents the result is the best performance among the models participating in the comparison