Thus, our specific contribution is a pipeline based on a cascade of deep neural network classifiers and multi-instance learning, which partly mimics the pathologist’ behaviour by first recognizing cancer and then evaluating HER2, and able to currently provide state-of-the-art performance for the novel problem of detecting HER2 from Haematoxylin–Eosin slides. The gene discussed is ERBB2; the disease is cancer.