TY - JOUR
T1 - Machine learning in laboratory medicine
T2 - Waiting for the flood?
AU - Cabitza, Federico
AU - Banfi, Giuseppe
PY - 2017/10/23
Y1 - 2017/10/23
N2 - 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.
AB - 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.
KW - artificial intelligence
KW - diagnostic aids
KW - literature review
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85032590324&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85032590324&partnerID=8YFLogxK
U2 - 10.1515/cclm-2017-0287
DO - 10.1515/cclm-2017-0287
M3 - Article
AN - SCOPUS:85032590324
JO - Clinical Chemistry and Laboratory Medicine
JF - Clinical Chemistry and Laboratory Medicine
SN - 1434-6621
ER -