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中药材及饮片检测中人工智能应用探讨

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目前,中药材及饮片的市场需求快速增长,其质量控制与安全保障更显迫切;传统的中药材及饮片检测手段存在主观经验依赖、检测精度有限、无法全面量化复杂成分等问题,难以满足中药材及饮片在准确分类与鉴别、精准成分测量等方面的需求,而人工智能技术的快速发展与广泛应用为中药材及饮片检测提供了新的解决方案.本文总结了中药材及饮片检测的现有方法及应用现状,系统梳理了人工智能技术在药材分类、真伪鉴别、产地溯源、有害成分测量、有效成分测量、药效测量等方面的典型应用,深入分析了当前面临的数据收集与标准化,检测数据共享机制,快速、无损、低成本检测技术需求,检测数据准确性,多模态检测数据融合等问题.研究认为,智能化、精准化、快速化是中药材及饮片检测未来的重点发展方向,需要持续完善检测标准与数据共享体系、深化人工智能技术研究与应用、强化多模态数据融合技术应用、引入新型传感技术、加强人工智能技术应用监管,以此推动我国中药材及饮片检测高质量发展,保障中医药产业的持续健康发展.
Applications of Artificial Intelligence in the Detection of Traditional Chinese Herbal Medicines and Prepared Slices
Currently,the market demand for traditional Chinese herbal medicines and prepared slices is experiencing rapid growth,rendering quality control and safety assurance even more pressing issues.Conventional testing methods for traditional Chinese herbal medicines and prepared slices,which are heavily reliant on subjective experience,limited in detection precision,and unable to comprehensively quantify complex constituents,are increasingly inadequate in satisfying the requirements for accurate classification,differentiation,and precise measurement of components in these materials.The rapid development and widespread application of artificial intelligence(AI),however,offer novel solutions for the testing of the traditional Chinese herbal medicines and prepared slices.This study summarizes the existing methods and current status of testing for the traditional Chinese herbal medicines and prepared slices,sorts out the typical applications of AI in medicinal material classification,authenticity identification,traceability of origin,harmful ingredient measurement,effective ingredient measurement,and medicinal effect measurement,and analyzes the current problems regarding data collection and standardization;sharing of testing data;demands for rapid,non-destructive,low-cost testing technologies;accuracy of testing data;and fusion of multi-modal testing data.The study believes that intelligence,precision,and speed are the key development directions for the testing of the traditional Chinese herbal medicines and prepared slices.To this end,we propose the following suggestions:continuously improving the testing standards and data sharing system,deepening the research and application of AI,strengthening the application of multi-modal data fusion technology,introducing new sensor technologies,and enhancing the supervision over AI applications,so as to promote the high-quality development of testing for traditional Chinese herbal medicines and prepared slices,and ensure the continuous and healthy development of the traditional Chinese medicine industry.

traditional Chinese herbal medicinetraditional Chinese medicine prepared slicesartificial intelligenceintelligent detection

王超超、张先超、谷正昌、王阶

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嘉兴大学信息网络与智能研究院,浙江嘉兴 314001

浙江省医学电子与数字健康重点实验室,浙江嘉兴 314001

全省多模态感知与智能系统重点实验室,浙江嘉兴 314001

上海大学计算机工程与科学学院,上海 200444

中国中医科学院广安门医院,北京 100053

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中药材 中药饮片 人工智能 智能检测

中国工程院咨询项目浙江省"鲲鹏行动"计划

2023-HY-10

2024

中国工程科学
中国工程院,高等教育出版社有限公司

中国工程科学

CSTPCD北大核心
影响因子:0.737
ISSN:1009-1742
年,卷(期):2024.26(2)
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