Nathan Radakovich1, Matthew Nagy1, Aziz Nazha2,3. 1. Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA. 2. Center for Clinical Artificial Intelligence, Cleveland Clinic, Cleveland, OH, USA. nazhaa@ccf.org. 3. Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Desk R35 9500 Euclid Ave., Cleveland, OH, 44195, USA. nazhaa@ccf.org.
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. 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.
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. 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.
Keywords:
Artificial intelligence; Deep learning; Hematology; Machine learning
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