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A systematic literature review of data science, data analytics and machine learning applied to healthcare engineering systems

Roberto Salazar-Reyna (Department of Engineering, Universidad de Monterrey, San Pedro Garza Garcia, Mexico)
Fernando Gonzalez-Aleu (Department of Engineering, Universidad de Monterrey, San Pedro Garza Garcia, Mexico)
Edgar M.A. Granda-Gutierrez (Graduate School of Engineering and Technology, Universidad de Monterrey, San Pedro Garza Garcia, Mexico)
Jenny Diaz-Ramirez (Department of Engineering, Universidad de Monterrey, San Pedro Garza Garcia, Mexico)
Jose Arturo Garza-Reyes (Centre for Supply Chain Improvement, University of Derby, Derby, UK)
Anil Kumar (Guildhall School of Business and Law, London Metropolitan University, London, UK)

Management Decision

ISSN: 0025-1747

Article publication date: 7 December 2020

Abstract

Purpose

The objective of this paper is to assess and synthesize the published literature related to the application of data analytics, big data, data mining and machine learning to healthcare engineering systems.

Design/methodology/approach

A systematic literature review (SLR) was conducted to obtain the most relevant papers related to the research study from three different platforms: EBSCOhost, ProQuest and Scopus. The literature was assessed and synthesized, conducting analysis associated with the publications, authors and content.

Findings

From the SLR, 576 publications were identified and analyzed. The research area seems to show the characteristics of a growing field with new research areas evolving and applications being explored. In addition, the main authors and collaboration groups publishing in this research area were identified throughout a social network analysis. This could lead new and current authors to identify researchers with common interests on the field.

Research limitations/implications

The use of the SLR methodology does not guarantee that all relevant publications related to the research are covered and analyzed. However, the authors' previous knowledge and the nature of the publications were used to select different platforms.

Originality/value

To the best of the authors' knowledge, this paper represents the most comprehensive literature-based study on the fields of data analytics, big data, data mining and machine learning applied to healthcare engineering systems.

Keywords

Citation

Salazar-Reyna, R., Gonzalez-Aleu, F., Granda-Gutierrez, E.M.A., Diaz-Ramirez, J., Garza-Reyes, J.A. and Kumar, A. (2020), "A systematic literature review of data science, data analytics and machine learning applied to healthcare engineering systems", Management Decision, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/MD-01-2020-0035

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited