6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Data Mining in Healthcare: Applying Strategic Intelligence Techniques to Depict 25 Years of Research Development

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In order to identify the strategic topics and the thematic evolution structure of data mining applied to healthcare, in this paper, a bibliometric performance and network analysis (BPNA) was conducted. For this purpose, 6138 articles were sourced from the Web of Science covering the period from 1995 to July 2020 and the SciMAT software was used. Our results present a strategic diagram composed of 19 themes, of which the 8 motor themes (‘NEURAL-NETWORKS’, ‘CANCER’, ‘ELETRONIC-HEALTH-RECORDS’, ‘DIABETES-MELLITUS’, ‘ALZHEIMER’S-DISEASE’, ‘BREAST-CANCER’, ‘DEPRESSION’, and ‘RANDOM-FOREST’) are depicted in a thematic network. An in-depth analysis was carried out in order to find hidden patterns and to provide a general perspective of the field. The thematic network structure is arranged thusly that its subjects are organized into two different areas, (i) practices and techniques related to data mining in healthcare, and (ii) health concepts and disease supported by data mining, embodying, respectively, the hotspots related to the data mining and medical scopes, hence demonstrating the field’s evolution over time. Such results make it possible to form the basis for future research and facilitate decision-making by researchers and practitioners, institutions, and governments interested in data mining in healthcare.

          Related collections

          Most cited references85

          • Record: found
          • Abstract: not found
          • Article: not found

          ImageNet classification with deep convolutional neural networks

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045

            Since the year 2000, IDF has been measuring the prevalence of diabetes nationally, regionally and globally.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              An introduction to ROC analysis

                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                17 March 2021
                March 2021
                : 18
                : 6
                : 3099
                Affiliations
                [1 ]Graduate Program of Industrial Systems and Processes, University of Santa Cruz do Sul, Santa Cruz do Sul 96816-501, Brazil; maikel.kolling@ 123456gmail.com (M.L.K.); sott.mk@ 123456gmail.com (M.K.S.)
                [2 ]Department of Industrial Engineering, Federal University of Rio Grande do Sul, Porto Alegre 90035-190, Brazil; leonardofurstenau@ 123456mx2.unisc.br
                [3 ]Department of Medicine, University of Santa Cruz do Sul, Santa Cruz do Sul 96816-501, Brazil; brunarabbaioli@ 123456gmail.com
                [4 ]Department of Computer Science, University of Santa Cruz do Sul, Santa Cruz do Sul 96816-501, Brazil; pedroh.u@ 123456hotmail.com
                [5 ]Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada
                Author notes
                Author information
                https://orcid.org/0000-0001-8984-7774
                https://orcid.org/0000-0002-7428-3993
                https://orcid.org/0000-0003-1844-8420
                https://orcid.org/0000-0001-8409-868X
                https://orcid.org/0000-0003-3010-8197
                Article
                ijerph-18-03099
                10.3390/ijerph18063099
                8002654
                33802880
                ae492c5f-affd-41f6-8e1e-1dfda788bc2e
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 January 2021
                : 15 March 2021
                Categories
                Article

                Public health
                data mining,industry 4.0,healthcare 4.0,bibliometrics,science mapping,strategic intelligence,co-word analysis,scimat

                Comments

                Comment on this article