Artificial Intelligence in Hematology: Current Challenges and Opportunities.

Journal: Current hematologic malignancy reports

Published Date: Jun 1, 2020

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.

Authors

Nathan Radakovich

Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, United States.
Matthew Nagy

Cleveland Clinic Lerner College of Medicine Case Western Reserve University Cleveland Ohio USA.
Aziz Nazha

Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, United States; Department of Hematology and Medical Oncology, Cleveland Clinic, United States; Center for Clinical Artificial Intelligence, Cleveland Clinic, United States. Electronic address: nazhaa@ccf.org.

Keywords

Artificial Intelligence Clinical Decision-Making Deep Learning Diagnosis, Computer-Assisted Hematology Humans Machine Learning Therapy, Computer-Assisted

External Resources

View on PubMed Access via DOI PubMed (32239350)

Artificial Intelligence in Hematology: Current Challenges and Opportunities.

Abstract

Authors

Keywords

External Resources

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