The manual examination of blood and bone marrow specimens for leukemia patients is time-consuming and limited by intra- and inter-observer variance. The development of AI algorithms for leukemia diagnostics requires high-quality sample digitization and reliable annotation of large datasets. Deep learning-based algorithms using these datasets attain human-level performance for some well-defined, clinically relevant questions such as the blast character of cells. Methods such as multiple …