Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Gu D

PROVIDER: S-EPMC7064966 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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

Gu Dongxiao D Yang Xuejie X Deng Shuyuan S Liang Changyong C Wang Xiaoyu X Wu Jiao J Guo Jingjing J

Journal of medical Internet research 20200225 2

<h4>Background</h4>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 ...[more]

PMID: 32130115

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Project description:BackgroundOne of the requirements for scientists and researchers to enter any field of science is to have a comprehensive and accurate understanding of that discipline.ObjectiveThis study aims to draw a science map, provide structural analysis, explore the evolution, and determine new trends in research articles published in the field of breast cancer.MethodsThis study comprised a descriptive survey with a scientometric approach. Data were collected from MEDLINE using a search strategy based on Medical Subject Heading (MeSH) terms. This study used science mapping, which provides a visual representation and a longitudinal evolution of possible interrelations between scientific areas, documents, or authors, thus reflecting the cognitive architecture of science mapping. For this scientometric evaluation of the topic of breast cancer research, a very long period was considered for data collection. Moreover, due to the availability of numerous publications in the database, the assessment was divided into three different periods ranging from 1988 to 2020.ResultsA total of 12,577 records related to scientometric studies were extracted. The field of breast cancer research demonstrated three diagrams containing the most relevant themes for the three chronological periods evaluated. Each diagram was plotted based on the centrality and density linked to each research topic. The research output in the field was observed to revolve around 8 areas or themes: radiation injury, cardiovascular disease, fibroadenoma, antineoplastic agent, estrogen antagonistic, immunohistochemistry, soybean, and epitopes, each represented with different colors.ConclusionsIn the strategic diagrams, the themes were both well developed and important for the structuring of a research field. The first quadrant comprised motor themes of the specialty, which present strong centrality and high density (eg, corticosteroid antineoplastic age, stem cell, T-lymphocyte, protein tyrosine kinase, dietary, and phosphatidyl inositol-3-kinase). In the second quadrant of diagram, themes have well-developed internal ties but unimportant external ties, as they are of only marginal importance for the field. These themes are very specialized and peripheral (eg, DNA-binding). In the third quadrant, themes are both weakly developed and marginal. The themes in this quadrant have low density and centrality and mainly represent either emerging or declining themes (eg, ovarian neoplasm). Themes in the fourth quadrant of the strategic diagram are considered important for a research field but are not fully developed. This quadrant contains transversal and general, basic themes (eg, immunohistochemistry). Scientometric analysis of breast cancer research can be regarded as a roadmap for future research and policymaking for this important field.

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Dataset Information

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

Publications

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

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