Therefore, the current study aims to evaluate and compare the potential of tumor-associated glycans Lea/c/x, sdi-Lea, sLea, sLex and sTn, and mucins MUC1 and MUC5AC for molecular imaging of PDAC using a semi-automated, machine learning-based digital image analysis workflow. The gene discussed is MUC5AC; the disease is neoplasm.