Shandong University of Traditional Chinese Medicine, Ministry of Education of China, Key Laboratory of Theory of TCM, Jinan 250355, China.
J AOAC Int. 2021 Dec 11;104(6):1754-1759. doi: 10.1093/jaoacint/qsab002.
The nature of Chinese herbal medicines (CHMs) is a bridge between traditional Chinese medicine and clinical application. Accurate nature identification of CHMs is essential for guiding the clinical application of CHMs.
To develop a new method for nature identification of CHMs according to compounds in CHMs.
The nature of a CHM is a comprehensive manifestation of the properties of various compounds in the CHM. In this study, 2012 CHM compounds were extracted to construct a compound data set. Molecular descriptors were utilized to build an identification model for classification of the cold-hot-neutral nature of CHM compounds.
The predictive accuracy and confusion matrix were validated using the assembled data set. The best model produced accuracies of 96.5 ± 0.5% and 86.5 ± 1.5% on training set and test set, respectively. Furthermore, the identification model is robust in predicting the cold-hot-neutral nature of CHM compounds.
This work shows how a classification model for medical nature identification can be developed. The derived model can be utilized for the application of CHMs.
To construct a nature identification model for analysis of the cold-hot-neutral nature of CHMs according to the compounds in CHMs.
中药的药性是连接中医理论与临床应用的桥梁。准确鉴定中药的药性对于指导中药的临床应用至关重要。
根据中药中的化合物开发一种中药药性鉴定的新方法。
中药的药性是中药中各种化合物性质的综合表现。本研究提取了 2012 种中药化合物，构建了一个化合物数据集。利用分子描述符建立了一个识别模型，用于分类中药化合物的寒、热、中性。
使用组合数据集验证了预测精度和混淆矩阵。最佳模型在训练集和测试集上的准确率分别为 96.5±0.5%和 86.5±1.5%。此外，该鉴定模型在预测中药化合物的寒、热、中性方面具有稳健性。
本研究展示了如何根据中药中的化合物构建一个用于分析中药寒、热、中性的分类模型。该模型可用于中药的应用。
根据中药中的化合物构建中药药性分析的鉴定模型。
