Combination of Principal Component Analysis and Bayesian Network and its Application on Syndrome Classification for Chronic Gastritis in Traditional Chinese Medicine

2007 ◽  
Author(s):  
Fengmei Zou ◽  
Changjun Li ◽  
Xueqin Hu ◽  
Changle Zhou
Keyword(s):  
Principal Component Analysis ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Bayesian Network ◽  
Chronic Gastritis ◽  
Principal Component ◽  
Component Analysis ◽  
Syndrome Classification

Establishment and comparative analysis of HPLC fingerprints of deer tissues

2020 ◽  
Vol 60 (10) ◽  
pp. 1343
Author(s):  
Mengjie Yao ◽  
Haiping Zhao ◽  
Xiaoyan Qi ◽  
Yuan Xu ◽  
Wenyuan Liu ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Evaluation System ◽  
High Performance ◽  
Principal Component ◽  
Component Analysis ◽  
Chemometric Methods

Context With the increasing use of velvet antlers (VA) as functional food or traditional Chinese medicine, the quality control has become more and more important. Aims Establish an effective method to provide a way of distinguishing VA from other types of deer tissue. Methods In the present study, 18 samples from three types of deer tissue were analysed on the basis of high-performance liquid chromatography, and a chromatogram of each sample was obtained. Then, these chromatograms were processed using the similarity evaluation system for chromatographic fingerprints of traditional Chinese medicine, to give the fingerprints of three deer tissues. The chemometric methods were used to analyse the fingerprint results, so as to identify the three types of deer tissue. Key results Shared peaks of VA, venison and deer bone were identified using similarity evaluation system. The results showed that, in total, 19 peaks were identified among these three types of deer tissue. Compared with venison, VA lacked three peaks (Numbers 3, 4 and 17); compared with deer bone, VA had six extra peaks (Numbers 2, 5, 8, 9, 14 and 19). The results of chemometric methods showed that different tissue samples could be classified into three categories by using both cluster analysis and principal component analysis. After principal component analysis and partial least-square discrimination analysis, seven peaks were selected, which had significant influence on the classification of VA, venison and deer bone. Conclusions The high-performance liquid-chromatography fingerprints in combination with chemometric methods can be used to effectively distinguish three deer tissue types, namely, VA, venison and deer bone. Implications We believe the method offers a useful tool much needed in the current Chinese velvet market.

Using Principal Component Analysis to Aid Bayesian Network Development for Prediction of Critical Care Patient Outcomes

2011 ◽  
Vol 71 (6) ◽  
pp. 1841-1849 ◽  
Author(s):  
Cindy Crump ◽  
Christine Tsien Silvers ◽  
Bruce Wilson ◽  
Loretta Schlachta-Fairchild ◽  
Colleen A. Lingley-Papadopoulos ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Critical Care ◽  
Bayesian Network ◽  
Patient Outcomes ◽  
Principal Component ◽  
Critical Care Patient ◽  
Component Analysis ◽  
Care Patient ◽  
Network Development
Sign in / Sign up

Export Citation Format

Share Document