Literature DB >> 33671623

Has the Flood Entered the Basement? A Systematic Literature Review about Machine Learning in Laboratory Medicine.

Luca Ronzio1, Federico Cabitza1, Alessandro Barbaro2, Giuseppe Banfi2,3.   

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.

Entities:  

Keywords:  deep learning; laboratory medicine; laboratory tests; machine learning

Year:  2021        PMID: 33671623     DOI: 10.3390/diagnostics11020372

Source DB:  PubMed          Journal:  Diagnostics (Basel)        ISSN: 2075-4418


  3 in total

1.  Current Issues, Challenges, and Future Perspectives in Clinical Laboratory Medicine.

Authors:  Ferdinando Mannello; Mario Plebani
Journal:  J Clin Med       Date:  2022-01-26       Impact factor: 4.241

Review 2.  Big Data in Laboratory Medicine-FAIR Quality for AI?

Authors:  Tobias Ueli Blatter; Harald Witte; Christos Theodoros Nakas; Alexander Benedikt Leichtle
Journal:  Diagnostics (Basel)       Date:  2022-08-09

Review 3.  Clinlabomics: leveraging clinical laboratory data by data mining strategies.

Authors:  Xiaoxia Wen; Ping Leng; Jiasi Wang; Guishu Yang; Ruiling Zu; Xiaojiong Jia; Kaijiong Zhang; Birga Anteneh Mengesha; Jian Huang; Dongsheng Wang; Huaichao Luo
Journal:  BMC Bioinformatics       Date:  2022-09-24       Impact factor: 3.307

  3 in total

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