Current evidence demonstrates that artificial intelligence can improve the high interobserver variability commonly seen in biomarker evaluation (ie, estimation of Ki67 scoring in breast cancer and tumour-infiltrating lymphocyte scoring in melanoma).29 The participants agreed that the pathologist’s visual assessment is subjective in assessing the degree of luminal occlusion, and they feel that there is scope to reduce the interobserver variability of this assessment through the increasing use of digital pathology. This evidence concerns the gene MKI67 and neoplasm.