We demonstrate the use of deep-learning–based image analysis (IA) of digitized tissue sections as a more sensitive, highly granular, and quantitative approach to quantify HER2 protein levels of expression throughout its entire spectrum, allowing for an improved patient stratification in T-DXd–treated BC samples. The gene discussed is ERBB2; the disease is breast cancer.