Bibliometric Insights of Global Research Landscape in Mitophagy

Li, Guoli; Yin, Wei; Yang, Yiya; Yang, Hongyu; Chen, Yinyin; Liang, Yumei; Zhang, Weiru; Xie, Tingting

doi:10.3389/fmolb.2022.851966

Cited by 7 publications

(5 citation statements)

References 78 publications

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“…This indicates that they have produced more in-depth studies in this field. The promotion of research in a certain field can be attributed to two important factors: governmental expenditure on healthcare and inter regional cooperation (Li et al, 2022). The USA spends $10,202 per capita on healthcare, outpacing most countries (Martin et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Research landscape and emerging trends of diabetes-associated cognitive dysfunction: a bibliometric analysis

Liang

Zhu

et al. 2023

Front. Neurosci.

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BackgroundDiabetes-associated cognitive dysfunction (DACD) is a common and serious complication in diabetes and has a high impact on the lives of both individuals and society. Although a number of research has focused on DACD in the past two decades, there is no a study to systematically display the knowledge structure and development of the field. Thus, the present study aimed to show the landscape and identify the emerging trends of DACD research for assisting researchers or clinicians in grasping the knowledge domain faster and easier and focusing on the emerging trends in the field.MethodsWe searched the Web of Science database for all DACD-related studies between 2000 and 2022. Bibliometric analysis was conducted using the VOSviewer, CiteSpace, Histcite, and R bibliometric package, revealing the most prominent research, countries, institutions, authors, journals, co-cited references, and keywords.ResultsA total of 4,378 records were selected for analysis. We found that the volume of literature on DACD has increased over the years. In terms of the number of publications, the USA ranked first. The most productive institutions were the University of Washington and the University of Pittsburgh. Furthermore, Biessels GJ was the most productive author. Journal of Alzheimers Disease, Diabetes Care, and Frontiers in Aging Neuroscience had the most publications in this field. The keywords“dementia,” “alzheimers-disease,” “cognitive impairment” and “diabetes” are the main keywords. The burst keywords in recent years mainly included “signaling pathway” and “cognitive deficit.”ConclusionThis study systematically illustrated advances in DACD over the last 23 years. Current findings suggest that exploring potential mechanisms of DACD and the effect of anti-diabetes drugs on DACD are the hotspots in this field. Future research will also focus on the development of targeted drugs that act on the DACD signaling pathway.

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Section: Discussionmentioning

confidence: 99%

Research landscape and emerging trends of diabetes-associated cognitive dysfunction: a bibliometric analysis

Liang

Zhu

et al. 2023

Front. Neurosci.

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“…Our data was preprocessed before analysis, and the specific steps were as follows: (1) Firstly, we imported the data into CiteSpace for deduplication ( 23 ); (2) Secondly, we converted the format of the data in CiteSpace ( 24 ); (3) Finally, we cleaned the data. In the country analysis, Wales, Scotland, North Ireland, and England were classified as the UK, and Taiwan was classified as China ( 25 ). In terms of institutions, for the organization of writing unification, such as, Univ Texas Southwestern med CTR Dalla was classified as Univ Texas SW med CTR Dallas; In keywords analysis, synonymous keywords were merged, ( 26 ) such as intensive care unit (ICU)was classified intensive care unit, acute kidney injury (AKI) was classified acute kidney injury.…”

Section: Methodsmentioning

confidence: 99%

Research frontiers and trends in the application of artificial intelligence to sepsis: A bibliometric analysis

Tang

Zhao

et al. 2023

Front. Med.

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BackgroundWith the increasing interest of academics in the application of artificial intelligence to sepsis, thousands of papers on this field had been published in the past few decades. It is difficult for researchers to understand the themes and latest research frontiers in this field from a multi-dimensional perspective. Consequently, the purpose of this study is to analyze the relevant literature in the application of artificial intelligence to sepsis through bibliometrics software, so as to better understand the development status, study the core hotspots and future development trends of this field.MethodsWe collected relevant publications in the application of artificial intelligence to sepsis from the Web of Science Core Collection in 2000 to 2021. The type of publication was limited to articles and reviews, and language was limited to English. Research cooperation network, journals, cited references, keywords in this field were visually analyzed by using CiteSpace, VOSviewer, and COOC software.ResultsA total of 8,481 publications in the application of artificial intelligence to sepsis between 2000 and 2021 were included, involving 8,132 articles and 349 reviews. Over the past 22 years, the annual number of publications had gradually increased exponentially. The USA was the most productive country, followed by China. Harvard University, Schuetz, Philipp, and Intensive Care Medicine were the most productive institution, author, and journal, respectively. Vincent, Jl and Critical Care Medicine were the most cited author and cited journal, respectively. Several conclusions can be drawn from the analysis of the cited references, including the following: screening and identification of sepsis biomarkers, treatment and related complications of sepsis, and precise treatment of sepsis. Moreover, there were a spike in searches relating to machine learning, antibiotic resistance and accuracy based on burst detection analysis.ConclusionThis study conducted a comprehensive and objective analysis of the publications on the application of artificial intelligence in sepsis. It can be predicted that precise treatment of sepsis through machine learning technology is still research hotspot in this field.

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“…Compared with traditional reviews, this study based on bibliometric tools provides better insights into the research hotspots and trends in the field of gastric cancer prediction, and the data analysis from various aspects is relatively more comprehensive and objective 31 . However, due to the limitations of software and research methods, the selected articles are limited to the WOS-CC database, and articles included in other databases (such as PubMed and Chinese databases) have not been retrieved.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Bibliometrics of gastric cancer prediction models

Gao,

Wang,

Xifeng

et al. 2024

Preprint

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Background: Bibliometric analysis highlights the key topics and publications in gastric cancer prediction. This paper analyzes the manuscripts in the field of gastric cancer (GC) prediction, guiding clinical work and prevention of GC. Methods: Using a search strategy, we retrieved research articles related to GC prognosis from the WOS core database: TS=((gastric cancer OR stomach cancer) AND (survival rate OR survival analysis OR prognosis) AND (predict model)). We set the language to English, the document type to article and review, and completed the search on July 1, 2023. We obtained 1598 relevant articles, and two researchers screened the search results again, excluding irrelevant, misclassified, and retracted articles. Any controversial articles were reviewed by a third researcher to make the final decision on the required literature. We finally selected 1056 articles, excluding 542 articles, and extracted the required data from the WOS database for analysis. The extracted database included: title, publication year, author, country, institution, citation count, journal, keyword, and reference. We used R (4.3.0) to load the R package (bibliometrix) for bibliometric analysis. Results: The 1056 articles came from 273 sources (journals, books, etc.), and 3661 authors conducted relevant research on GC prognosis models. Oncology Frontiers published the most articles (N=72), and Gastric Cancer Journal had the most citations (N=1130). The publication time span ranged from 1991 to 2023, with an average annual growth rate of 13.31%. The number of publications increased from 2017, with a sharp increase from 2020 to 2023. The five countries with the most publications were China (n = 826), Japan (n = 62), Korea (n = 47), USA (n = 42), Italy (n = 19) and 1998 (n = 10). China had the most citations (N=9595), and USA had the highest average citation per article (44.9 times). The most common topic was GC survival (n=236), followed by expression (n=209). Conclusion: Multiple GC prediction models in this study describe the science of predicting GC incidence and prognosis. This work provides the most influential references related to GC prediction and serves as a guide for citable papers.

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Bibliometric Insights of Global Research Landscape in Mitophagy

Cited by 7 publications

References 78 publications

Research landscape and emerging trends of diabetes-associated cognitive dysfunction: a bibliometric analysis

Research landscape and emerging trends of diabetes-associated cognitive dysfunction: a bibliometric analysis

Research frontiers and trends in the application of artificial intelligence to sepsis: A bibliometric analysis

Bibliometrics of gastric cancer prediction models

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