应用于肝癌临床研究的机器学习全球趋势：文献计量与可视化分析（2001 - 2024年）
Global trends in machine learning applied to clinical research in liver cancer: Bibliometric and visualization analysis (2001-2024).
作者信息
Zhuo Enba, Yang Wenzhi, Wang Yafen, Tang Yanchao, Wang Wanrong, Zhou Lingyan, Chen Yanjun, Li Pengman, Chen Bangjie, Gao Weimin, Liu Wang
机构信息
Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
First Clinical College, Anhui Medical University, Hefei, China.
出版信息
Medicine (Baltimore). 2024 Dec 6;103(49):e40790. doi: 10.1097/MD.0000000000040790.
This study explores the intersection of liver cancer and machine learning through bibliometric analysis. The aim is to identify highly cited papers in the field and examine the current research landscape, highlighting emerging trends and key areas of focus in liver cancer and machine learning. By analyzing citation patterns, this study sheds light on the evolving role of machine learning in liver cancer research and its potential for future advancements.
本研究通过文献计量分析探讨肝癌与机器学习的交叉领域。目的是识别该领域中被高度引用的论文，并审视当前的研究状况，突出肝癌和机器学习领域的新兴趋势及重点关注领域。通过分析引用模式，本研究揭示了机器学习在肝癌研究中不断演变的作用及其未来发展的潜力。
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