Artificial intelligence in bone marrow histological diagnostics: potential applications and challenges

The expanding digitalization of routine diagnostic histological slides holds a potential to apply artificial intelligence (AI) to pathology, including bone marrow (BM) histology. In this perspective we describe potential tasks in diagnostics that can be supported, investigations that can be guided and questions that can be answered by the future application of AI on whole slide images of BM biopsies. These range from characterization of cell lineages and quantification of cells and stromal structures to disease prediction. First glimpses show an exciting potential to detect subtle phenotypic changes with AI that are due to specific genotypes. The discussion is illustrated by examples of current AI research using BM biopsy slides. In addition, we briefly discuss current challenges for implementation of AI-supported diagnostics.

Automated summary

The increasing digitalization of routine diagnostic histological slides provides the potential to apply artificial intelligence (AI) in pathology, specifically in bone marrow histology. This perspective explores the potential tasks, investigations, and questions that can be addressed by applying AI to whole slide images of bone marrow biopsies. The discussion includes examples of current AI research using bone marrow biopsy slides and briefly touches upon the challenges of implementing AI-supported diagnostics.