中药质量标准的可控性与科学性是保障中药临床疗效的核心要素，现阶段传统质量标准的核心局限在于中药整体性与还原性之间的矛盾，这使得中药质量标准难以获得以还原论为主导的国际认可，进而严重阻碍了中药的国际化进程。而张量作为一种可处理复杂高维数据的数理工具，其在人工智能和大数据技术领域的应用，能够显著提升计算效率，推动复杂AI模型与应用的实现。此外，张量在高维数据建模方面的理论和算法研究，为解决实际问题提供了关键的数学工具。通过应用2阶张量校正法和3阶张量校正法，可以对中药成分进行精确的分析，从而建立宏观中药质量与微观成分之间的逻辑关联，有效解决中药质量整体性与还原性之间的矛盾。因此张量技术有望为中药质量标准现代化提供新的理论支持和技术手段。

The controllability and scientific rigor of traditional Chinese medicine (TCM) quality standards are fundamental to ensuring their clinical efficacy. The core limitation of current TCM quality standards lies in the inherent conflict between holistic and reductionist approaches, which hinders their international recognition under reductionist frameworks and significantly impedes TCM’s globalization. As a mathematical tool for processing complex high-dimensional data, tensor theory demonstrates exceptional computational efficiency when applied in artificial intelligence (AI) and big data technologies, thereby accelerating the development of sophisticated AI models and applications. Furthermore, tensor-based theoretical and algorithmic research in high-dimensional data modeling provides essential mathematical tools for practical problem-solving. By applying the second-order tensor correction method and the third-order tensor correction method, we can accurately analyze the components of TCM, thus establishing the logical relationship between the macro-quality of TCM and the micro-components, and effectively solving the contradiction between the integrity and reducibility of TCM quality. Therefore, tensor technology is expected to provide new theoretical support and technical means for the modernization of quality standards of TCM.

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国家自然科学基金项目（81874344）；湖南省卫生健康高层次人才重大科研专项（R2023139）；湖南省自然科学基金项目（2023JJ60474）；;长沙市自然科学基金项目（kq2208191）；湖南创新型省份建设专项（2024RC8110）