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Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis

BACKGROUND: With the continuous development of the internet and the explosive growth in data, big data technology has emerged. With its ongoing development and application, cloud computing technology provides better data storage and analysis. The development of cloud health care provides a more conv...

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Detalles Bibliográficos
Autores principales: Gu, Dongxiao, Yang, Xuejie, Deng, Shuyuan, Liang, Changyong, Wang, Xiaoyu, Wu, Jiao, Guo, Jingjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064966/
https://www.ncbi.nlm.nih.gov/pubmed/32130115
http://dx.doi.org/10.2196/15142
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author Gu, Dongxiao
Yang, Xuejie
Deng, Shuyuan
Liang, Changyong
Wang, Xiaoyu
Wu, Jiao
Guo, Jingjing
author_facet Gu, Dongxiao
Yang, Xuejie
Deng, Shuyuan
Liang, Changyong
Wang, Xiaoyu
Wu, Jiao
Guo, Jingjing
author_sort Gu, Dongxiao
collection PubMed
description BACKGROUND: With the continuous development of the internet and the explosive growth in data, big data technology has emerged. With its ongoing development and application, cloud computing technology provides better data storage and analysis. The development of cloud health care provides a more convenient and effective solution for health. Studying the evolution of knowledge and research hotspots in the field of cloud health care is increasingly important for medical informatics. Scholars in the medical informatics community need to understand the extent of the evolution of and possible trends in cloud health care research to inform their future research. OBJECTIVE: Drawing on the cloud health care literature, this study aimed to describe the development and evolution of research themes in cloud health care through a knowledge map and common word analysis. METHODS: A total of 2878 articles about cloud health care was retrieved from the Web of Science database. We used cybermetrics to analyze and visualize the keywords in these articles. We created a knowledge map to show the evolution of cloud health care research. We used co-word analysis to identify the hotspots and their evolution in cloud health care research. RESULTS: The evolution and development of cloud health care services are described. In 2007-2009 (Phase I), most scholars used cloud computing in the medical field mainly to reduce costs, and grid computing and cloud computing were the primary technologies. In 2010-2012 (Phase II), the security of cloud systems became of interest to scholars. In 2013-2015 (Phase III), medical informatization enabled big data for health services. In 2016-2017 (Phase IV), machine learning and mobile technologies were introduced to the medical field. CONCLUSIONS: Cloud health care research has been rapidly developing worldwide, and technologies used in cloud health research are simultaneously diverging and becoming smarter. Cloud–based mobile health, cloud–based smart health, and the security of cloud health data and systems are three possible trends in the future development of the cloud health care field.
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spelling pubmed-70649662020-03-19 Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis Gu, Dongxiao Yang, Xuejie Deng, Shuyuan Liang, Changyong Wang, Xiaoyu Wu, Jiao Guo, Jingjing J Med Internet Res Original Paper BACKGROUND: With the continuous development of the internet and the explosive growth in data, big data technology has emerged. With its ongoing development and application, cloud computing technology provides better data storage and analysis. The development of cloud health care provides a more convenient and effective solution for health. Studying the evolution of knowledge and research hotspots in the field of cloud health care is increasingly important for medical informatics. Scholars in the medical informatics community need to understand the extent of the evolution of and possible trends in cloud health care research to inform their future research. OBJECTIVE: Drawing on the cloud health care literature, this study aimed to describe the development and evolution of research themes in cloud health care through a knowledge map and common word analysis. METHODS: A total of 2878 articles about cloud health care was retrieved from the Web of Science database. We used cybermetrics to analyze and visualize the keywords in these articles. We created a knowledge map to show the evolution of cloud health care research. We used co-word analysis to identify the hotspots and their evolution in cloud health care research. RESULTS: The evolution and development of cloud health care services are described. In 2007-2009 (Phase I), most scholars used cloud computing in the medical field mainly to reduce costs, and grid computing and cloud computing were the primary technologies. In 2010-2012 (Phase II), the security of cloud systems became of interest to scholars. In 2013-2015 (Phase III), medical informatization enabled big data for health services. In 2016-2017 (Phase IV), machine learning and mobile technologies were introduced to the medical field. CONCLUSIONS: Cloud health care research has been rapidly developing worldwide, and technologies used in cloud health research are simultaneously diverging and becoming smarter. Cloud–based mobile health, cloud–based smart health, and the security of cloud health data and systems are three possible trends in the future development of the cloud health care field. JMIR Publications 2020-02-25 /pmc/articles/PMC7064966/ /pubmed/32130115 http://dx.doi.org/10.2196/15142 Text en ©Dongxiao Gu, Xuejie Yang, Shuyuan Deng, Changyong Liang, Xiaoyu Wang, Jiao Wu, Jingjing Guo. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.02.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Gu, Dongxiao
Yang, Xuejie
Deng, Shuyuan
Liang, Changyong
Wang, Xiaoyu
Wu, Jiao
Guo, Jingjing
Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis
title Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis
title_full Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis
title_fullStr Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis
title_full_unstemmed Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis
title_short Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis
title_sort tracking knowledge evolution in cloud health care research: knowledge map and common word analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064966/
https://www.ncbi.nlm.nih.gov/pubmed/32130115
http://dx.doi.org/10.2196/15142
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