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      Bibliometric analysis of researches on traditional Chinese medicine for coronavirus disease 2019 (COVID-19)

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          Abstract

          Background

          The coronavirus disease 2019 (COVID-19) has caused a worldwide pandemic, and traditional Chinese medicine (TCM) has played an important role in response. We aimed to analyze the published literature on TCM for COVID-19, and provide reference for later research.

          Methods

          This study searched the CBM, CNKI, PubMed, and EMBASE from its establishment to March 11, 2020. VOSviewer 1.6.11 and gCLUTO 2.0 software were used to visually analyze the included studies.

          Results

          A total of 309 studies were included, including 61 journals, 1441 authors, 277 institutions, and 27 provinces. Cooperation among regions was closer, but the teamwork of institutions and authors were more likely to be confined to the same region. Among the authors with frequency greater than two (65 authors), only 19 authors who had connection with others. More than 70% (358/491) of keywords only presented once, and 20 keywords shown more than 10 times. Five research topics were identified: Data mining method based analysis on the medication law of Chinese medicine in prevention and management of COVID-19, exploration of active compounds of Chinese medicine for COVID-19 treatment based on network pharmacology and molecular docking, expert consensus and interpretation of COVID-19 treatment, research on the etiology and pathogenesis of COVID-19, and clinical research of TCM for COVID-19 treatment.

          Conclusion

          The research hotspots were scattered, and the collaboration between authors and institutions needed to be further strengthened. To improve the quality and efficiency of research output, the integration of scientific research and resources, as well as scientific collaboration is needed.

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          Most cited references24

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          Is Open Access

          The bibliometric analysis of scholarly production: How great is the impact?

          Bibliometric methods or “analysis” are now firmly established as scientific specialties and are an integral part of research evaluation methodology especially within the scientific and applied fields. The methods are used increasingly when studying various aspects of science and also in the way institutions and universities are ranked worldwide. A sufficient number of studies have been completed, and with the resulting literature, it is now possible to analyse the bibliometric method by using its own methodology. The bibliometric literature in this study, which was extracted from Web of Science, is divided into two parts using a method comparable to the method of Jonkers et al. (Characteristics of bibliometrics articles in library and information sciences (LIS) and other journals, pp. 449–551, 2012: The publications either lie within the Information and Library Science (ILS) category or within the non-ILS category which includes more applied, “subject” based studies. The impact in the different groupings is judged by means of citation analysis using normalized data and an almost linear increase can be observed from 1994 onwards in the non-ILS category. The implication for the dissemination and use of the bibliometric methods in the different contexts is discussed. A keyword analysis identifies the most popular subjects covered by bibliometric analysis, and multidisciplinary articles are shown to have the highest impact. A noticeable shift is observed in those countries which contribute to the pool of bibliometric analysis, as well as a self-perpetuating effect in giving and taking references.
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            • Record: found
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            Is Open Access

            Visualizing a field of research: A methodology of systematic scientometric reviews

            Systematic scientometric reviews, empowered by computational and visual analytic approaches, offer opportunities to improve the timeliness, accessibility, and reproducibility of studies of the literature of a field of research. On the other hand, effectively and adequately identifying the most representative body of scholarly publications as the basis of subsequent analyses remains a common bottleneck in the current practice. What can we do to reduce the risk of missing something potentially significant? How can we compare different search strategies in terms of the relevance and specificity of topical areas covered? In this study, we introduce a flexible and generic methodology based on a significant extension of the general conceptual framework of citation indexing for delineating the literature of a research field. The method, through cascading citation expansion, provides a practical connection between studies of science from local and global perspectives. We demonstrate an application of the methodology to the research of literature-based discovery (LBD) and compare five datasets constructed based on three use scenarios and corresponding retrieval strategies, namely a query-based lexical search (one dataset), forward expansions starting from a groundbreaking article of LBD (two datasets), and backward expansions starting from a recently published review article by a prominent expert in LBD (two datasets). We particularly discuss the relevance of areas captured by expansion processes with reference to the query-based scientometric visualization. The method used in this study for comparing bibliometric datasets is applicable to comparative studies of search strategies.
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              Bibliometric analysis of global research on PD-1 and PD-L1 in the field of cancer

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                Author and article information

                Contributors
                Journal
                Integr Med Res
                Integr Med Res
                Integrative Medicine Research
                Elsevier
                2213-4220
                2213-4239
                29 July 2020
                29 July 2020
                : 100490
                Affiliations
                [a ]Evidence-based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China
                [b ]Evidence-based Medicine Center, Tianjin University of Traditional Chinese Medicine, Tianjin, China
                [c ]Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
                [d ]Dongfang Hospital Beijing University of Chinese Medicine, Beijing, China
                Author notes
                [* ]Corresponding author at: Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Chengguan District, Lanzhou City, Gansu province, 730000, China. zjhtcm@ 123456foxmail.com tianjh@ 123456lzu.edu.cn
                [1]

                Evidence-Based Medicine Center, Tianjin University of Traditional Chinese Medicine, No. 312 Anshanxi Street, Nankai District, Tianjin, 300193, China

                Article
                S2213-4220(20)30122-0 100490
                10.1016/j.imr.2020.100490
                7387281
                32802744
                f43b6105-6710-4a28-8c08-3394add4e610
                .

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 13 June 2020
                : 16 July 2020
                : 16 July 2020
                Categories
                Article

                covid-19,traditional chinese medicine,bibliometrics,visual analysis

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