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杨文静, 吕章艳, 冯小双, 王维, 任建松, 池慧, 杜然然. 人工智能在癌症研究领域的文献可视化分析[J]. 肿瘤防治研究, 2021, 48(2): 133-139. DOI: 10.3971/j.issn.1000-8578.2020.20.0657
引用本文: 杨文静, 吕章艳, 冯小双, 王维, 任建松, 池慧, 杜然然. 人工智能在癌症研究领域的文献可视化分析[J]. 肿瘤防治研究, 2021, 48(2): 133-139. DOI: 10.3971/j.issn.1000-8578.2020.20.0657
YANG Wenjing, LYV Zhangyan, FENG Xiaoshuang, WANG Wei, REN Jiansong, CHI Hui, DU ranran. Visualization Analysis of Literatures About Artificial Intelligence in Cancer Research[J]. Cancer Research on Prevention and Treatment, 2021, 48(2): 133-139. DOI: 10.3971/j.issn.1000-8578.2020.20.0657
Citation: YANG Wenjing, LYV Zhangyan, FENG Xiaoshuang, WANG Wei, REN Jiansong, CHI Hui, DU ranran. Visualization Analysis of Literatures About Artificial Intelligence in Cancer Research[J]. Cancer Research on Prevention and Treatment, 2021, 48(2): 133-139. DOI: 10.3971/j.issn.1000-8578.2020.20.0657

人工智能在癌症研究领域的文献可视化分析

Visualization Analysis of Literatures About Artificial Intelligence in Cancer Research

  • 摘要:
    目的 分析Web of Science核心合集数据库2010—2019年人工智能在癌症研究领域的文献,总结研究热点和发展趋势。
    方法 通过文献计量学方法和CiteSpace信息可视化软件,对2010—2019年Web of Science核心合集数据库关于人工智能在癌症研究领域的相关文献进行可视化分析。
    结果 人工智能在癌症研究领域的发文量逐年上升,美国在此领域的发文量、被引频次及合作能力均排在首位,中国的发文量虽排在第二位但被引频次较低。人工智能在癌症研究的热点领域主要在乳腺癌和肺癌,通过机器学习、神经网络等方法构建模型,应用于癌症的基础研究和临床诊断、治疗及预后预测等方面。人工智能的方法学研究、对癌症发生和分类的研究以及蛋白质研究是该领域的研究前沿。
    结论 通过借鉴国际研究的热点与前沿技术,注重国际合作与国家级机构间合作,加强交叉学科研究,将有效促进中国人工智能在癌症研究方面的发展。

     

    Abstract:
    Objective To analyze the literatures about artificial intelligence in cancer research in Web of Science (WOS) core collection database in 2010-2019 and summarize research hot spots and development trends.
    Methods Through bibliometrics methods and CiteSpace information visualization software, we applied the visual analysis of relevant literature on artificial intelligence in the field of cancer research retrieved from the Web of Science core collection database from 2010 to 2019.
    Results The number of published articles about artificial intelligence in the field of cancer research had been increasing year by year. The United States ranked first in the number of published articles in this field, the number of citations and cooperation capabilities. Although the number of published articles in China ranked the second, the number of citations was low. The hot spots of artificial intelligence in cancer research were mainly breast cancer and lung cancer. Machine learning, neural network and other methods were used to build models, which were used in basic cancer research, clinical diagnosis, treatment and prognosis prediction. The research frontiers were the methodological research of artificial intelligence, the research on the occurrence and classification of cancer and the research of protein in this field.
    Conclusion It will effectively promote the development of artificial intelligence in cancer research in China by learning the hot spots and cutting-edge technologies of international research, focusing on international cooperation and cooperation among national institutions and strengthening cross-disciplinary research.

     

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