Artificial Intelligence in Hematology: Current Challenges and Opportunities

Current Hematologic Malignancy Reports
Nathan RadakovichAziz Nazha

Abstract

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. 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. 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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Related Concepts

Clinical Decision-Making
Transfer Learning (machine activity)
Deep Learning
Knowledge Acquisition (Computer)
Computer Assisted Diagnosis
Hematology (Discipline)
Homo sapiens
Therapy, Computer-Assisted
Diagnosis
Hematology (Discipline)

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