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Integrating image and gene-data with a semi-supervised attention model for prediction of KRAS gene mutation status in non-small cell lung cancer

Table 5

Comparison of classification performance of UNet, ResNet, ResNeXt, Inception-v3 and SE-ResNeXt on S²MMAM.

SE-ResNeXt(Ours) achieved the best results in all six comparative metrics.

doi: https://doi.org/10.1371/journal.pone.0297331.t005