通过使用机器学习方法对全球癌症研究进行文献计量分析
Lianghong Lin1, Likeng Liang2, Maojie Wang3,4,5
1School of Artificial Intelligence South China Normal University Guangzhou China.
Cancer innovation
|December 13, 2023
概括
癌症研究中的机器学习正在迅速发展. 这项研究分析了6206篇文章,揭示了深度学习和支持矢量机器等关键主题,并突出了美国.
科学领域:
- 计算生物学是一种计算生物学.
- 生物信息学是一种生物信息学.
- 医疗信息学医学信息学
背景情况:
- 由于计算机技术的进步,癌症研究中的机器学习 (ML) 应用正在扩大.
- 了解当前的景观,趋势和合作对于未来的进步至关重要.
研究的目的:
- 对2011-2021年癌症研究中的ML进行文献计量分析.
- 识别研究现状,趋势,主题,合作和未来方向.
主要方法:
- 对6206篇PubMed文章 (2011-2021) 的图书统计分析.
- 使用Python进行文献计量,使用Gephi进行社交网络分析,以及使用Latent Dirichlet Allocation进行话题建模.
主要成果:
- 该领域表现出强的发展和日益增长的影响,在ML-癌症交叉点出现了重大创新.
- 自然通讯 (有影响力) 和科学报告 (多产) 是主要的期刊.
- 美国和哈佛大学是主要贡献者.
- 核心研究主题包括支持矢量机,分类和深度学习.
结论:
- 该研究提供了关于ML在癌症研究中的动态发展和趋势的见解.
- 结果帮助研究人员和从业人员了解研究热点和潜在的未来方向.
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