机器学习应用到肝癌临床研究中的全球趋势:图书识别和可视化分析 (2001-2024)
Enba Zhuo1, Wenzhi Yang2, Yafen Wang3
1Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Medicine
|December 10, 2024
概括
这项研究使用文献识别分析来绘制肝癌中机器学习的研究格局. 它确定了关键的论文和趋势,揭示了机器学习.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 数据科学数据科学数据科学
背景情况:
- 肝癌是一个重大的全球健康挑战.
- 机器学习 (ML) 为分析复杂的生物医学数据提供了强大的工具.
- 将ML整合到肝癌研究中是一个快速发展的领域.
研究的目的:
- 在肝癌研究中对机器学习应用进行文献分析.
- 确定这个跨学科领域的开创性和高度引用的出版物.
- 绘制当前的研究格局,趋势和未来的方向.
主要方法:
- 科学文献的图书统计分析.
- 引用网络分析.
- 关键词同时出现的分析.
- 出版产出的趋势分析.出版产出的趋势分析.
主要成果:
- 确定关键的研究集群和有影响力的论文.
- 绘制应用到肝癌的机器学习技术演变的地图.
- 突出新兴趋势,如深度学习和预测建模.
结论:
- 机器学习越来越多地成为肝癌研究的组成部分.
- 图书计量分析为研究动态和影响提供了宝贵的见解.
- 未来的进步在于继续整合和创新用于肝癌诊断,预后和治疗的ML方法.
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