Machine learning in laboratory medicine: waiting for the flood?

Machine learning in laboratory medicine: waiting for the flood? AbstractThis review focuses on machine learning and on how methods and models combining data analytics and artificial intelligence have been applied to laboratory medicine so far. Although still in its infancy, the potential for applying machine learning to laboratory data for both diagnostic and prognostic purposes deserves more attention by the readership of this journal, as well as by physician-scientists who will want to take advantage of this new computer-based support in pathology and laboratory medicine. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Clinical Chemistry and Laboratory Medicine (CCLM) de Gruyter

Machine learning in laboratory medicine: waiting for the flood?

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Publisher
De Gruyter
Copyright
©2018 Walter de Gruyter GmbH, Berlin/Boston
ISSN
1437-4331
eISSN
1437-4331
D.O.I.
10.1515/cclm-2017-0287
Publisher site
See Article on Publisher Site

Abstract

AbstractThis review focuses on machine learning and on how methods and models combining data analytics and artificial intelligence have been applied to laboratory medicine so far. Although still in its infancy, the potential for applying machine learning to laboratory data for both diagnostic and prognostic purposes deserves more attention by the readership of this journal, as well as by physician-scientists who will want to take advantage of this new computer-based support in pathology and laboratory medicine.

Journal

Clinical Chemistry and Laboratory Medicine (CCLM)de Gruyter

Published: Mar 28, 2018

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