碳化
线性判别分析
计算机科学
材料科学
傅里叶变换红外光谱
模式识别(心理学)
工艺工程
人工智能
工程类
化学工程
扫描电子显微镜
复合材料
作者
Mingliang Gao,Yi Zhang,Fang-Fang Cheng,Wang Hang-Hang,Liu Ling-Run,Xin Jin,Yanan Zhou,Tianshu Wang,Peidong Chen,Weifeng Yao,Beihua Bao,Zhang Li
标识
DOI:10.1016/j.saa.2021.120363
摘要
Carbonized traditional Chinese medicine (TCM) is a kind of distinctive traditional drug which has been widely used in various bleeding syndromes for over two thousand years, and most of them are still in clinical use. Although they share similar processing method: stir-frying, there are no specific quality standards and few quality control researches carried out on carbonized TCM up until now. Carbonized Typhae Pollen (CTP) is a typical carbonized TCM with efficacy of eliminating blood stasis and stanching bleeding. In this study, a novel process quality control model coupled with near infrared spectroscopy was established, called Gradient-based Discriminant Analysis method (GDA). Compared with conventional modeling methods (Convolutional Neural Network, Linear Discriminant Analysis, Standard Normal Variate-LDA), GDA model applied in fiber optic probe acquisition mode exhibited highest test accuracy (0.961), satisfactory correct identification (internal validation, 100%; external validation, 97.1%) and excellent model stability. This method provided a perfect guideline for process quality control of Carbonized TCM as well as ensured their clinical efficacy.
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