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

Elisa Lin, Franklin Fuda, Hung S. Luu, Andrew M. Cox, Fengqi Fang, Junlin Feng, Mingyi Chen

Research output: Contribution to journalReview articlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)88-94
Number of pages7
JournalSeminars in Diagnostic Pathology
Issue number2
StatePublished - Mar 2023


  • AI
  • Digital pathology
  • Hematology laboratory

ASJC Scopus subject areas

  • Pathology and Forensic Medicine


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