This 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.

Cabitza, F., Banfi, G. (2018). Machine learning in laboratory medicine: Waiting for the flood?. CLINICAL CHEMISTRY AND LABORATORY MEDICINE, 56(4), 516-524 [10.1515/cclm-2017-0287].

Machine learning in laboratory medicine: Waiting for the flood?

Cabitza, F
;
Banfi, G
2018

Abstract

This 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.
Articolo in rivista - Review Essay
artificial intelligence; diagnostic AIDS; literature review; machine learning;
artificial intelligence; diagnostic aids; literature review; machine learning; Clinical Biochemistry; Biochemistry (medical)
English
2018
56
4
516
524
none
Cabitza, F., Banfi, G. (2018). Machine learning in laboratory medicine: Waiting for the flood?. CLINICAL CHEMISTRY AND LABORATORY MEDICINE, 56(4), 516-524 [10.1515/cclm-2017-0287].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/185242
Citazioni
  • Scopus 82
  • ???jsp.display-item.citation.isi??? 60
Social impact