This article presents a systematic literature review that expands and updates a previous review on the application of machine learning to laboratory medicine. We used Scopus and PubMed to collect, select and analyse the papers published from 2017 to the present in order to highlight the main studies that have applied machine learning techniques to haematochemical parameters and to review their diagnostic and prognostic performance. In doing so, we aim to address the question we asked three years ago about the potential of these techniques in laboratory medicine and the need to leverage a tool that was still under-utilised at that time.

Ronzio, L., Cabitza, F., Barbaro, A., Banfi, G. (2021). Has the flood entered the basement? A systematic literature review about machine learning in laboratory medicine. DIAGNOSTICS, 11(2) [10.3390/diagnostics11020372].

Has the flood entered the basement? A systematic literature review about machine learning in laboratory medicine

Cabitza F.
Co-primo
;
Banfi G.
Ultimo
2021

Abstract

This article presents a systematic literature review that expands and updates a previous review on the application of machine learning to laboratory medicine. We used Scopus and PubMed to collect, select and analyse the papers published from 2017 to the present in order to highlight the main studies that have applied machine learning techniques to haematochemical parameters and to review their diagnostic and prognostic performance. In doing so, we aim to address the question we asked three years ago about the potential of these techniques in laboratory medicine and the need to leverage a tool that was still under-utilised at that time.
Articolo in rivista - Articolo scientifico
Deep learning; Laboratory medicine; Laboratory tests; Machine learning;
English
2021
11
2
372
open
Ronzio, L., Cabitza, F., Barbaro, A., Banfi, G. (2021). Has the flood entered the basement? A systematic literature review about machine learning in laboratory medicine. DIAGNOSTICS, 11(2) [10.3390/diagnostics11020372].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/399463
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