A big data platform that allows tracing supply chain of herbs used in TCM to ensure market reliability and improve supply chains.
Led by the Traditional Chinese Medicine Resource Center of the Chinese Academy of Chinese Medical Sciences, the project aims to improve the overall efficiency of the Traditional Chinese Medicine (TCM) market by the isotopic analysis of the composition and attached soil of Chinese herbal medicine, and matching with data provided by the big data platform of Chinese geographic, to understand the origin of Chinese medicine. Based on LDA, PCA, KNN, and other machine learning algorithms, the model was able to understand the influence of various supply chains in producing the herbs used in TCM.
Some of methods include:
– Multidimensional quantitative characterization analysis of soil characteristics of TCM by using recursive feature elimination method with the correlation of multiple variables, and a multidimensional quantitative description system for soil characteristics of TCM;
– Multi-component analysis of quality factors of TCM based on multispectral technology. Intelligent high-level calibration analysis strategy for non-target metabolic profile component analysis, the artificial intelligence analysis of multidimensional data, extraction of key characteristic variable factors (characteristic markers, metabolites) of medicinal material quality;
– An adaptive mathematical model of the variable factor regulation network of soil characteristics and TCM quality, with an exploration of the interaction of its variable factors, and construct the relationship between soil characteristics (physical, chemical and biological characteristics) of exemplary authentic medicinal materials and its quality factors.