传统医学中的人工智能:证据,障碍和个性化护理研究路线图
Ketmanee Jongjiamdee1, Pimnipa Pornwonglert1, Nutnichar Na Bangchang1
1Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Frontiers in artificial intelligence
|September 25, 2025
概括
人工智能 (AI) 正在增强传统医学 (TM) 的诊断和个性化护理. 需要进一步的研究和标准,以确保安全和公平地将人工智能整合到阿育吠陀,中国传统医学和泰国传统医学中.
科学领域:
- 综合医学是一个整体的医学.
- 计算健康科学 计算健康科学
- 数字健康数字健康
背景情况:
- 传统医学 (TM) 系统如阿育吠陀,中国传统医学 (TCM) 和泰国传统医学 (TTM) 越来越多地与人工智能 (AI) 进行整合.
- 这个交叉点旨在利用人工智能来推进TM实践.
- 整合旨在提高TM框架内的可访问性,有效性和研究.
研究的目的:
- 综合人工智能在TM中的当前应用.
- 识别阻碍在TM中采用AI的障碍.
- 概述安全,公平和可扩展的AI整合到TM的研究需求.
主要方法:
- 针对2017年至2025年8月的同行评审研究进行了有针对性的叙述性小审查.
- 在PubMed,Scopus和Google Scholar中使用与TM (阿育吠陀,TCM,TTM) 和AI (机器学习,NLP,计算机视觉,远程医疗) 相关的关键词进行的搜索.
- 纳入标准侧重于研究报告的方法和绩效指标,不包括没有数据的评论和预印.
主要成果:
- 人工智能协助诊断模式识别和个性化框架使用多源数据.
- 人工智能支持数字知识保存,远程医疗,在TM中进行草药学/安全评估.
- 绩效指标有所不同,取决于上下文,外部验证有限.
结论:
- 人工智能有可能扩大TM教育,研究和临床服务.
- 为了取得进步,需要制定标准,文化相关的数据集,前性试验和明确的治理.
- 提出了一个研究路线图,以严格和道德地将AI整合到TM中.
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