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Global Trend on Machine Learning in Helicobacter within One Decade: A Scientometric Study.

Global health, epidemiology and genomics(2023)

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摘要
A total of 17,413 articles were reviewed and analyzed, with descriptive characteristics of the literature included. In journals, 21,102 keywords plus and 20,490 author keywords were reported. These articles were also written by 56,106 different authors, with 262 being single-author articles. Most authors' abstracts, titles, and keywords included "Helicobacter-pylori." Since 2010, the total number of -related publications has been decreasing. Gut, PLOS ONE, and Gastroenterology are the most influential journals, according to source impact. China, the United States, and Japan are the countries with most affiliations and subjects. In addition, Seoul National University has published the most articles about . According to the cloud word plot, the authors' most frequently used keywords are gastric cancer (GC), , gastritis, eradication, and inflammation. "" and "infection" have the steepest slopes in terms of the upward trend of words used in articles from 2010 to 2021. Subjects such as GC, intestinal metaplasia, epidemiology, peptic ulcer, eradication, and clarithromycin are included in the diagram's motor theme section, according to strategic diagrams. According to the thematic evolution map, topics such as infection, B-cell lymphoma, CagA, , and infection were largely discussed between 2010 and 2015. From 2016 to 2021, the top topics covered included , infection, and infection.
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关键词
helicobacter,machine learning
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