A Bibliometric Analysis of Personal Protective Equipment and COVID-19 Researches

Hu, Man; Wang, Junwu; Wang, Pingchuan; Shi, Pengzhi; Zhao, Wenjie; Liu, Xin; Peng, Qing; Meng, Bo; Feng, Xinmin; Zhang, Liang

doi:10.3389/fpubh.2022.855633

Cited by 11 publications

(10 citation statements)

References 41 publications

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“…1,26 These technologies are extensively employed in a variety of scientific domains, from micro (institutional level) to macro (global level), and can be evaluated qualitatively and quantitatively. 27 This study is the first bibliometric study focusing on AI and spine and visual mapping. The findings of this study may aid in collating data and obtaining the greatest yield data for AI and spine field research, revealing the field's development trend and understanding its future path.…”

Section: Discussionmentioning

confidence: 99%

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A Bibliometric Analysis of Artificial Intelligence Applications in Spine Care

Zhang

Zhao

et al. 2023

J Neurol Surg A Cent Eur Neurosurg

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Background With the rapid development of science and technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis analysis of various spine diseases. It has been proved that AI has a broad prospect in the accurate diagnosis and treatment of spine field. Methods On May 07, 2022, the Web of Science (WOS) Core Collection database was used to identify the documents on the application of AI in spine field. HistCite and VOSviewer softwares were used for citation analysis and visualization mapping. Results A total of 693 documents were included in the final analysis. The most prolific authors were Karhade AV and Schwab JH. The USA was the most productive country. The leading journal was Spine. The most frequently used keyword was spinal. The most prolific institution was Northwestern Univ. Network visualization map showed that USA was the largest network of international cooperation. The keyword “machine learning” had the strongest total link strengths (TLS) and largest number of occurrences. The latest trends suggest that AI for the diagnosis of spine diseases may receive widespread attention in the future. Conclusions AI has a wide range of application prospect in the subject of spine field, and an increasing number of scholars are committed to the research of AI in spine field. Bibliometric analysis in the field of AI and spine provides an overall perspective, and the appreciation and research of these influential publications are useful for future research.

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Section: Discussionmentioning

confidence: 99%

“…To begin, just WOS was utilized to do literature searches, rather than Google academic, Medline, or other databases. 27 The number of citations in the report might change somewhat. Second, English was included in the language selection, which may result in the exclusion of articles in other languages that are relevant.…”

Section: Limitationmentioning

confidence: 99%

A Bibliometric Analysis of Artificial Intelligence Applications in Spine Care

Zhang

Zhao

et al. 2023

J Neurol Surg A Cent Eur Neurosurg

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“…Although many bibliometric studies [ 11 – 15 ] have been published on COVID-19, none of them discuss the link between the illness and antibiotic use. However, since this is one of the most compelling hypotheses about AMR, it is important to identify potential developments that could provide researchers with direction when designing new studies [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

The state of current research on COVID-19 and antibiotic use: global implications for antimicrobial resistance

Zyoud

2023

J Health Popul Nutr

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Background During the initial stages of the coronavirus disease 2019 (COVID-19) pandemic, the administration of antibiotics to patients was prevalent in numerous countries. Despite this, the rising threat of antimicrobial resistance (AMR) presents a significant public health concern. The escalation of AMR has been exacerbated by the ongoing COVID-19 pandemic. Against this backdrop, the primary aim of this study was to conduct a bibliometric and visual analysis of research pertaining to the use of antibiotics in COVID-19. Methods This study examined documents indexed in Scopus between 2020 and 2022. To visualize the trends and hotspots of research related to antibiotics and COVID-19, as well as collaborative networks, the researcher utilized version 1.6.18 of the VOSviewer software. Scopus data were analysed to extract information on the types of publications, annual research output, countries, institutions, funding agencies, journals, citations, and highly cited references. Microsoft Excel 2019 was used to process and organize the extracted data. Results This study analysed 1137 documents related to COVID-19 and antibiotics and found that the number of publications increased from 130 in 2020 to 527 in 2022. These publications included 777 (68.34%) articles and 205 (18.03%) reviews. The top five countries in terms of scientific production were the United States (n = 231; 20.32%), the United Kingdom (n = 156; 13.72%), China (n = 101; 8.88%), India (n = 100; 8.8%), and Italy (n = 63; 5.54%), and the leading institutions were Imperial College London (n = 21; 1.85%), University of Oxford (n = 20; 1.76%), and University College London (n = 15; 1.32%). The National Natural Science Foundation of China provided funding for the highest number of articles (n = 48; 4.22%), followed by the National Institutes of Health (n = 32; 2.81%). The most productive journals were Antibiotics (n = 90; 7.92%), Journal of Antimicrobial Chemotherapy (n = 30; 2.64%), and Infection Control and Hospital Epidemiology (n = 26; 2.29%). Finally, the research hotspots identified in this study were ‘antimicrobial stewardship during the COVID-19 outbreak’ and ‘implications of the COVID-19 pandemic on the emergence of antimicrobial resistance.’ Conclusions This is the first bibliometric analysis of COVID-19-related research on antibiotics. Research was carried out in response to global requests to increase the fight against AMR and awareness of the issue. More restrictions on the use of antibiotics are urgently needed from policy makers and authorities, more so than in the current situation.

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“…Bibliometric analysis is a popular quantitative analysis method in many disciplines, which has been adopted by many scholars in the field of health so far. For example, it has been used in renal fibrosis in diabetic kidney disease ( 12 ), personal protective equipment in COVID-19 ( 13 ), and macrophages associated with acute lung injury ( 14 ). By visualizing the content and citations of published articles, this type of article can help readers gain a better understanding of research hotspots and identify future research directions in a particular research discipline.…”

Section: Introductionmentioning

confidence: 99%

Bibliometric analysis of global research trends on post-stroke pneumonia: Current development status and research Frontiers

Chen

2022

Front. Public Health

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BackgroundAs one of the most common complications of stroke, post-stroke pneumonia significantly increases the incidence of adverse outcomes, mortality, and healthcare costs for patients with stroke. As the field of post-stroke pneumonia has gained interest in the recent years, there has been an increasing number of publications on post-stroke pneumonia research worldwide. Therefore, a more comprehensive understanding of the field is needed now. This paper is intended to analyze the research status and detect the research frontiers in this field.MethodsVOS viewer, CiteSpace, and the online scientometric platform (https://bibliometric.com/) were the main visualization tools used in this paper. They were used to perform citation analysis of countries/institutions, co-citation analysis of authors/journals/references, co-authorship analysis of authors, co-occurrence analysis of keywords, and citation bursts analysis of references.ResultsThe number of publications in this field has increased rapidly since 2010 and is expected to continue to increase in the next few years. The countries contributing most to post-stroke pneumonia research were the USA, China, and Germany. The most productive institution was Harvard University, followed by Humboldt University of Berlin, Charité Universitätsmedizin Berlin, and Free University of Berlin from Germany. Meanwhile, the German authors Meisel A, Meisel C, and Dirnagl U, who have contributed significantly to this field, were all associated with these three German institutions. The high-quality and high output journal was STROKE. In the coming years, the hot topic keywords “risk & risk-factors,” “outcome & impact,” “management & guidelines,” and “predictors” will gain more attention in this field. Finally, hot keywords were grouped into four clusters in this paper: cluster 1 (risk-factors studies of post-stroke pneumonia), cluster 2 (clinically relevant studies of post-stroke pneumonia), cluster 3 (mechanism studies of post-stroke pneumonia), and cluster 4 (care studies of post-stroke pneumonia).ConclusionThis study shows the knowledge structure and evolution of the field of post-stroke pneumonia research and predicts research trends through visualization analysis. The future trend of post-stroke pneumonia research will gradually shift from clinical and mechanistic studies to treatment and prevention studies.

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A Bibliometric Analysis of Personal Protective Equipment and COVID-19 Researches

Cited by 11 publications

References 41 publications

A Bibliometric Analysis of Artificial Intelligence Applications in Spine Care

A Bibliometric Analysis of Artificial Intelligence Applications in Spine Care

The state of current research on COVID-19 and antibiotic use: global implications for antimicrobial resistance

Bibliometric analysis of global research trends on post-stroke pneumonia: Current development status and research Frontiers

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