利用人工智能的应用来识别传统中医药
Shunjiang Jia1, Huanling Lai2, Hailong Bai1
1College of Pharmacy, Shaanxi University of Chinese Medicine, Shiji Ave, Xi'an-xianyang New Economic Zone, Shaanxi Province, China.
Journal of ethnopharmacology
|October 6, 2025
概括
人工智能 (AI) 通过图像识别和毒性评估来增强中药 (CHM) 认证和质量控制. 在人工智能辅助传统中医药 (TCM) 开发的数据质量和标准化方面仍然存在挑战.
科学领域:
- 药理学和传统医学的医学.
- 计算机科学和人工智能 人工智能
背景情况:
- 人工智能 (AI) 集成为验证和控制中国草药 (CHM) 质量提供了新的解决方案.
- 人工智能解决了CHM分析中长期存在的挑战,朝着更客观和更有效的方法迈进.
研究的目的:
- 审查当前AI在CHM中的应用和局限性.
- 为未来人工智能辅助的传统中医 (TCM) 研究和实践提供指导.
主要方法:
- 在PubMed,谷歌学者和CNKI进行全面的文献搜索.
- 专注于人工智能在CHM图像识别,质量控制,原产地识别,植物化学分析和毒性评估中的应用.
主要成果:
- 人工智能显著提高了CHM识别的准确性和效率.
- 人工智能与光谱,感觉和染色学方法相结合,可以提高质量控制和毒性评估.
- 支持向量机 (SVM) 在原产地识别方面表现有前途,但数据大小和区域差异限制了概括性.
结论:
- 人工智能在CHM分析的各个方面,包括识别,质量控制和毒性评估,都显示出巨大的潜力.
- 克服数据质量,可解释性和监管批准方面的挑战对于推动TCM人工智能发展至关重要.
- 加强标准化和跨学科合作是未来在中国传统医学中人工智能发展的关键.
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