We demonstrate that state-of-the-art performance for predicting EGFR can be achieved by using attention-based models that evaluate a full range of tissue morphologies, outperforming our tumor-only models as well as those shown in prior literature (0.825–0.831 AUC)14. This evidence concerns the gene EGFR and neoplasm.