Because patients with germline BRCA1/2 mutations exhibit specific pathological features (e.g., absence of HR and HER2 expression[5, 22]), deep learning can help predict germline[17a] or somatic[16a]BRCA1/2 mutations in breast and ovarian cancer[3, 16] but is limited by small study cohorts,[17a] lack of external validation,[16a,c] and insufficient information on germline mutations.[3, 16] Notably, the clinical utility of AI‐based prescreening has been independently validated in other cancer types. The gene discussed is ERBB2; the disease is ovarian carcinoma.