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10.19540/j.cnki.cjcmm.20200320.501

http://scihub22266oqcxt.onion/10.19540/j.cnki.cjcmm.20200320.501
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32495576!ä!32495576

suck abstract from ncbi


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pmid32495576      Zhongguo+Zhong+Yao+Za+Zhi 2020 ; 45 (10): 2239-2248
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  • Visual analysis of coronavirus disease 2019 (COVID-19) studies based on bibliometrics #MMPMID32495576
  • Chen Y; Guo YB; Guo R; Chen XF; Chang GH; Li X; Hao LY; Sun ZR; Zhang ZL
  • Zhongguo Zhong Yao Za Zhi 2020[May]; 45 (10): 2239-2248 PMID32495576show ga
  • To analyze the development of coronavirus disease 2019(COVID-19), this study systematically retrieved relevant Chinese and English literatures from both CNKI and Web of Science database platforms by bibliometric research method and CiteSpace 5.5.R2 software to obtain information and visualize relevant literatures. A total of 695 Chinese and 446 English literatures were included in this paper. Statistics showed that China had published most of the literatures and established close cooperation with the United States and the United Kingdom. Through the analysis, Tongji Medical College of Huazhong University of Science and Technology and its affiliated hospitals published the largest number of the publications. Moreover, the highly productive journals including Journal of Traditional Chinese Medicine and The Lancet covered eight major fields, such as medicine, medical virology, radiation medicine, infectious disease, and traditional Chinese medicine. Besides, a total of 35 special COVID-19 funds were recently established to subsidize these studies. The key words and themes analysis indicated that protein structure of COVID-19, receptor targets and mechanisms of action, integration of traditional Chinese and Western medicine, screening and development of antiviral drugs from traditional Chinese medicine and Western medicine, vaccine research as well as epidemiological characteristics and prediction are current study hotspots. This study provides a reference for researchers to rapidly master main study directions of COVID-19 and screen out relevant literatures.
  • |*Betacoronavirus[MESH]
  • |*Bibliometrics[MESH]
  • |*Coronavirus Infections[MESH]
  • |*Pandemics[MESH]
  • |*Pneumonia, Viral[MESH]
  • |COVID-19[MESH]
  • |China[MESH]
  • |Humans[MESH]
  • |SARS-CoV-2[MESH]
  • |United Kingdom[MESH]


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