肺癌机器学习的进展和未来趋势:一个全面的文献计量分析
Wenhao Zhang1,2,3, Dongmei Zhuang4, Wenzhuo Wei2
1Department of Psychiatry, Chaohu Hospital of Anhui Medical University, Hefei, Anhui, China.
概括
机器学习 (ML) 显著推动了肺癌研究,美国在应用方面处于领先地位. 现在的主要趋势包括计算机辅助检测,生存预测和放射学,突出显示未来的研究方向.
科学领域:
- 医疗信息学 医疗信息学
- 在瘤学瘤学.
- 人工智能的人工智能
背景情况:
- 机器学习 (ML) 迅速推进了肺癌查,诊断和治疗.
- 机器学习的持续发展推动了瘤学研究的进展.
研究的目的:
- 系统地分析自2004年以来机器学习在肺癌研究中的演变.
- 确定该领域的核心驱动因素和新兴趋势.
主要方法:
- 从Web of Science核心收藏中对1826篇学术论文进行了图书统计分析.
- 分析作者,期刊和关键词共发生网络.
- 爆发引文分析,以确定不断发展的研究热点.
主要成果:
- 美国在肺癌研究的ML应用方面处于领先地位,哈佛大学是关键机构.
- 马达布希·安南特是重要的贡献者;SCI REP-UK发表了最多的论文.
- 研究趋势从"乳腺癌"和"放射治疗"演变为"计算机辅助诊断",最近又演变为"纹理分析"",计算机辅助检测"",生存预测"和"放射学".
结论:
- 机器学习越来越多地成为肺癌研究的组成部分.
- "计算机辅助检测"",生存预测"和"放射学"是关键的新兴领域.
- 这些重要领域需要更多的研究关注,以便在未来取得进展.
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