The algorithm, based on ResNet50, was trained using a multi-country dataset of 3474 patients (Australian Breast Cancer Tissue Bank and The Cancer Genome Atlas), and achieved AUCs of 0.92, 0.81, and 0.78, for ER, PgR, and HER2, respectively. The gene discussed is ERBB2; the disease is breast carcinoma.