Artificial intelligence and digital microscopy applications in diagnostic hematopathology

Hanadi El Achi, Joseph D. Khoury

Research output: Contribution to journalReview articlepeer-review

48 Scopus citations


Digital Pathology is the process of converting histology glass slides to digital images using sophisticated computerized technology to facilitate acquisition, evaluation, storage, and portability of histologic information. By its nature, digitization of analog histology data renders it amenable to analysis using deep learning/artificial intelligence (DL/AI) techniques. The application of DL/AI to digital pathology data holds promise, even if the scope of use cases and regulatory framework for deploying such applications in the clinical environment remains in the early stages. Recent studies using whole-slide images and DL/AI to detect histologic abnormalities in general and cancer in particular have shown encouraging results. In this review, we focus on these emerging technologies intended for use in diagnostic hematology and the evaluation of lymphoproliferative diseases.

Original languageEnglish (US)
Article number797
Issue number4
StatePublished - Apr 2020
Externally publishedYes


  • Artificial intelligence
  • Digital pathology
  • Hematopathology
  • Leukemia
  • Lymphoma

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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