Overview of our pipeline. (Left to right) Whole bone marrow smear scan images are processed using a CFM to automatically extract the most relevant single-cell crops, which are rudimentary classified into 4 cell classes. Subsequently, a GFEN is used to predict 5 genetic indicators that are important for first-line therapy decisions (CBFB::MYH11, MRC cytogenetics, FLT3^mut, NPM1^mut, and ELN 2017 favorable risk) based on appropriate single-cell images only. Additionally, visualization strategies were used to gain explainability with respect to the used deep learning models.