Digital pathology and artificial intelligence as the next chapter in diagnostic hematopathology

Digital pathology has a crucial role in diagnostic pathology and is increasingly a technological requirement in the field. Integration of digital slides into the pathology workflow, advanced algorithms, and computer-aided diagnostic techniques extend the frontiers of the pathologist's view beyond the microscopic slide and enable true integration of knowledge and expertise. There is clear potential for artificial intelligence (AI) breakthroughs in pathology and hematopathology. In this review article, we discuss the approach of using machine learning in the diagnosis, classification, and treatment guidelines of hematolymphoid disease, as well as recent progress of artificial intelligence in flow cytometric analysis of hematolymphoid diseases. We review these topics specifically through the potential clinical applications of CellaVision, an automated digital image analyzer of peripheral blood, and Morphogo, a novel artificial intelligence-based bone marrow analyzing system. Adoption of these new technologies will allow pathologists to streamline workflow and achieve faster turnaround time in diagnosing hematological disease.

Automated summary

Digital pathology plays a crucial role in diagnostic pathology and is becoming increasingly essential in the field. By integrating digital slides, advanced algorithms, and computer-aided techniques, pathologists can extend their view beyond microscopic slides and integrate knowledge and expertise. Artificial intelligence (AI) holds great potential for breakthroughs in pathology and hematopathology. This review discusses the use of machine learning in diagnosis, classification, and treatment guidelines of hematolymphoid disease, as well as recent progress in AI-based flow cytometric analysis. Adoption of new technologies like CellaVision and Morphogo allows pathologists to streamline workflow and achieve faster diagnoses of hematological diseases.