期刊
DIAGNOSTICS
卷 11, 期 2, 页码 -出版社
MDPI
DOI: 10.3390/diagnostics11020372
关键词
laboratory medicine; machine learning; deep learning; laboratory tests
This article presents a systematic literature review on the application of machine learning in laboratory medicine, focusing on studies from 2017 to the present that have utilized machine learning techniques to analyze haematochemical parameters for diagnostic and prognostic purposes. The review aims to address the potential of these techniques in laboratory medicine and the under-utilization of this tool in the past.
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.
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