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Artificial Intelligence in Hematology: Current Challenges and Opportunities

  • Social Media Impact of Hematologic Malignancies (N Pemmaraju, Section Editor)
  • Published:
Current Hematologic Malignancy Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Artificial intelligence (AI), and in particular its subcategory machine learning, is finding an increasing number of applications in medicine, driven in large part by an abundance of data and powerful, accessible tools that have made AI accessible to a larger circle of investigators.

Recent Findings

AI has been employed in the analysis of hematopathological, radiographic, laboratory, genomic, pharmacological, and chemical data to better inform diagnosis, prognosis, treatment planning, and foundational knowledge related to benign and malignant hematology. As more widespread implementation of clinical AI nears, attention has also turned to the effects this will have on other areas in medicine.

Summary

AI offers many promising tools to clinicians broadly, and specifically in the practice of hematology. Ongoing research into its various applications will likely result in an increasing utilization of AI by a broader swath of clinicians.

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Authors and Affiliations

  1. Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA

    Nathan Radakovich & Matthew Nagy

  2. Center for Clinical Artificial Intelligence, Cleveland Clinic, Cleveland, OH, USA

    Aziz Nazha

  3. Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Desk R35 9500 Euclid Ave., Cleveland, OH, 44195, USA

    Aziz Nazha

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  1. Nathan Radakovich
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Correspondence to Aziz Nazha.

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This article is part of the Topical Collection on Social Media Impact of Hematologic Malignancies

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Radakovich, N., Nagy, M. & Nazha, A. Artificial Intelligence in Hematology: Current Challenges and Opportunities. Curr Hematol Malig Rep 15, 203–210 (2020). https://doi.org/10.1007/s11899-020-00575-4

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