传统中国医学中的机器学习研究趋势:一篇图书统计综述
Jiekee Lim1, Jieyun Li1, Mi Zhou1
1School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People's Republic of China.
International journal of general medicine
|November 26, 2024
概括
机器学习 (ML) 正在彻底改变中国传统医学 (TCM) 的诊断和治疗. 图书统计分析显示,TCM的ML应用快速增长,特别是在中国,增强了个性化医疗和质量控制.
科学领域:
- 综合医学是一个整体的医学.
- 计算生物学 计算生物学
- 图书统计学 图书统计学
背景情况:
- 传统中医 (TCM) 与现代技术,特别是机器学习 (ML) 的整合,为改善诊断和治疗提供了巨大的潜力.
- 在推进TCM研究和临床实践方面,ML应用越来越重要.
- 了解用于TCM的ML的趋势和发展对于其现代化至关重要.
研究的目的:
- 系统地审查和分析传统中医 (TCM) 中机器学习 (ML) 应用的趋势和发展.
- 在TCM研究中对ML进行文献计量分析.
- 确定关键的研究领域,领先的机构,以及在TCM中ML应用的地理分布.
主要方法:
- 从科学网络核心收藏 (2000-2023) 来源的474份文档的图书统计分析.
- 使用微软Office Excel,Bibliometrix和VOSviewer进行数据分析和可视化.
- 确定研究成果趋势,领先的国家,机构和研究热点.
主要成果:
- 从2000年到2023年,在TCM中ML的研究成果显著增加,中国是主要贡献者.
- 主要研究领域包括用于TCM诊断的ML,网络药理学和舌头诊断.
- 化学测量与ML相结合,在TCM产品质量控制和认证中占据着重要地位.
结论:
- ML集成正在推进TCM诊断,个性化医疗和质量控制,支持TCM现代化和国际化.
- 未来的研究应该优先考虑模型解释性,国际合作和标准化报告.
- 本文献计量分析提供了在TCM研究领域的ML的全面概述.
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