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对传统医学的最新人工智能进行了审查

Chengbin Hou¹, Yanzhuo Gao², Xinyu Lin¹

¹School of Computing and Artificial Intelligence, Fuyao University of Science and Technology, Fujian, 350109, China.

Journal of traditional and complementary medicine

|June 9, 2025

概括

传统医学的人工智能 (AITM) 集成了先进的AI技术,如机器学习和深度学习,以增强诊断和研究. 这种协同作用旨在提高医疗保健效率和患者的结果.

科学领域:

综合医学是一个整体的医学.
计算健康计算健康
生物医学信息学生物医学信息学

背景情况:

传统医学 (TM) 提供了一种具有悠久历史的整体医疗保健方法.
人工智能 (AI) 在数据挖掘,模式识别和决策方面提供了先进的能力.
人工智能和TM的融合,称为传统医学的人工智能 (AITM),代表了医疗保健的重大进步.

研究的目的:

探索人工智能技术在传统医学应用中的整合.
审查最近在机器学习,深度学习和大语言模型中的进展,应用于TM.
确定AITM在诊断和研究中的关键应用.

主要方法:

审查当前的人工智能方法,包括机器学习,深度学习和大型语言模型.
在TM诊断的各个阶段 (前,期间,后) 对AI应用的分析.
检查AI在TM研究中的作用,包括药物发现,知识结构和数据分析.

主要成果:

人工智能提高了决策效率,诊断准确度和TM患者体验.
人工智能驱动的方法可以优化TM研究,从药物开发到数据解释.
整合人工智能导致医疗保健提供潜在的成本降低.

结论:

AITM为推进传统医学诊断和研究提供了一个强大的框架.
本次审查旨在弥合AI和TM社区之间的差距,促进合作.
最终的目标是利用人工智能通过增强的TM实践来改善人类健康.

关键词:

为了健康,人工智能人工智能用于医学.人工智能的人工智能是人工智能.深度学习是一种深度学习.大型语言模型.机器学习是机器学习.传统医学是传统的医学.

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