To this effect, whole-tumor sections with low abundance of deep learning-predicted CA9+ epithelial cells (0–1%, n = 80) belonged predominantly (n = 74, 92%) to the Pathologist_Score_Negative (samples graded by pathologist as negative for epithelial CA9 expression) with few samples (n = 6, 8%) belonging to Pathologist_Score_positive (samples with varying degree of CA9 positivity). Here, CA9 is linked to neoplasm.