Dataset Information

A bibliometric analysis of 23,492 publications on rectal cancer by machine learning: basic medical research is needed.

ABSTRACT: Background and Aims:The aim of this study was to analyse the landscape of publications on rectal cancer (RC) over the past 25?years by machine learning and semantic analysis. Methods:Publications indexed in PubMed under the Medical Subject Headings (MeSH) term 'Rectal Neoplasms' from 1994 to 2018 were downloaded in September 2019. R and Python were used to extract publication date, MeSH terms and abstract from the metadata of each publication for bibliometric assessment. Latent Dirichlet allocation was applied to analyse the text from the articles' abstracts to identify more specific research topics. Louvain algorithm was used to establish a topic network resulting in identifying the relationship between the topics. Results:A total of 23,492 papers published were identified and analysed in this study. The changes of research focus were analysed by the changing of MeSH terms. Studied contents extracted from the publications were divided into five areas, including surgical intervention, radiotherapy and chemotherapy intervention, clinical case management, epidemiology and cancer risk as well as prognosis studies. Conclusions:The number of publications indexed on RC has expanded rapidly over the past 25?years. Studies on RC have mainly focused on five areas. However, studies on basic research, postoperative quality of life and cost-effective research were relatively lacking. It is predicted that basic research, inflammation and some other research fields might become the potential hotspots in the future.

SUBMITTER: Wang K

PROVIDER: S-EPMC7385823 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

A bibliometric analysis of 23,492 publications on rectal cancer by machine learning: basic medical research is needed.

Wang Kangtao K Feng Chenzhe C Li Ming M Pei Qian Q Li Yuqiang Y Zhu Hong H Song Xiangping X Pei Haiping H Tan Fengbo F

Therapeutic advances in gastroenterology 20200727

<h4>Background and aims</h4>The aim of this study was to analyse the landscape of publications on rectal cancer (RC) over the past 25 years by machine learning and semantic analysis.<h4>Methods</h4>Publications indexed in PubMed under the Medical Subject Headings (MeSH) term 'Rectal Neoplasms' from 1994 to 2018 were downloaded in September 2019. R and Python were used to extract publication date, MeSH terms and abstract from the metadata of each publication for bibliometric assessment. Latent Di ...[more]

PMID: 32782478

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Project description:BackgroundAlthough publications have been increasing rapidly, the research quality has yet to improve in the field of critical care medicine (CCM) in China. This study aimed at investigating the current status of and the influential factors for impactful publications in CCM research by Chinese authors.MethodsPublications by authors with the affiliation of critical care medicine department or intensive care unit (CCM/ICU) in Chinese as well as American hospitals from 2001 to 2020 were retrieved from the Web of Science Core Collection (WoSCC) database for this bibliometric analysis. Moreover, statistical analyses to test factors affecting impactful publications by Chinese authors were performed.ResultsOf 13,487 articles retrieved by this search strategy, 6,622 were published by Chinese authors as first or corresponding authors. The annual publications by Chinese authors have been rapidly increasing from 2001 to 2020, and so did the citations to these articles. However, the proportion in the world of publications by Chinese authors was much less than that by American authors each year [M (IQR): 1.85 (9.592) vs. 27.77 (7.3), p < 0.001]. In addition, impactful articles were significantly less published by Chinese than by American authors, including articles either in journals with a high impact factor (p < 0.001) or in the top 10 journals in the field of CCM (5.4 vs 13.4%, p < 0.001), and articles with high citation frequency as well (p < 0.001). Moreover, the percentage of impactful publications by Chinese authors was likely associated with academic background and regions of the author's affiliations, funds support, public health events of COVID-19, and collaboration between authors.ConclusionOur results demonstrated that CCM research in China grew rapidly in the recent 20 years. However, the impactful publications remained limited, largely owing to the shortage of comprehensive research training, inactive collaboration, and underfunded CCM research.

Dataset Information

A bibliometric analysis of 23,492 publications on rectal cancer by machine learning: basic medical research is needed.

Publications

A bibliometric analysis of 23,492 publications on rectal cancer by machine learning: basic medical research is needed.

Similar Datasets

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