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- W4313702900 abstract "Abstract Background Substantial improvements in computational power and machine learning (ML) algorithm development have vastly increased the limits of what autonomous machines are capable of. Since its beginnings in the 19th century, laboratory hematology has absorbed waves of progress yielding improvements in both of accuracy and efficiency. The next wave of change in laboratory hematology will be the result of the ML revolution that has already touched many corners of healthcare and society at large. Content This review will describe the manifestations of ML and artificial intelligence (AI) already utilized in the clinical hematology laboratory. This will be followed by a topical summary of the innovative and investigational applications of this technology in each of the major subdomains within laboratory hematology. Summary Application of this technology to laboratory hematology will increase standardization and efficiency by reducing laboratory staff involvement in automatable activities. This will unleash time and resources for focus on more meaningful activities such as the complexities of patient care, research and development, and process improvement." @default.
- W4313702900 created "2023-01-08" @default.
- W4313702900 creator A5039483069 @default.
- W4313702900 date "2023-01-04" @default.
- W4313702900 modified "2023-10-18" @default.
- W4313702900 title "Hematology and Machine Learning" @default.
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- W4313702900 doi "https://doi.org/10.1093/jalm/jfac108" @default.
- W4313702900 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36610431" @default.
- W4313702900 hasPublicationYear "2023" @default.
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