Houpo Quality Assessment Based on Data Mining and Defuzzification Gamma Distribution

2014 ◽  
Vol 513-517 ◽  
pp. 1633-1636
Author(s):  
Jian Yang Lin ◽  
Hui Zhou ◽  
Ming Yan Jiang
Keyword(s):  
Data Mining ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Plant Morphology ◽  
Quality Standard ◽  
Standard Test ◽  
Morphological Classification ◽  
Identification Methods ◽  
Sample Data

According to the traditional morphological classification, the Houbo quality of traditional chinese medicine is divided into recommended products and non-recommended products; Discrete the chromatography data of the Houbo which obtained under the condition of standard test and also make the data mining. Obtaining the great peaks of linear independent vectors and obtaining every clustering centre data of Houbo by the fuzzy and Defuzzification methods. Make Houbo criterion and sample data as weibull distribution to calculate similar. This research combines the plant morphology, chemistry, statistics and calculating technology to establish the pattern identification methods of quality and have good attempt to Chinese traditional machine quality methods. The research results provide the basis for quality standard revision of Houbo.

Huangbai Quality Assessment Based on Information Reduction and Defuzzification Weibull Distribution

2014 ◽  
Vol 513-517 ◽  
pp. 1629-1632
Author(s):  
Jian Yang Lin ◽  
Ming Yan Jiang ◽  
Hui Zhou
Keyword(s):  
Chinese Medicine ◽  
Weibull Distribution ◽  
Plant Morphology ◽  
Quality Standard ◽  
Standard Test ◽  
Morphological Classification ◽  
Identification Methods ◽  
Information Reduction ◽  
Sample Data

According to the traditional morphological classification, the Huangbai quality of traditional chinese medicine is divided into recommended products and non-recommended products; Discrete the chromatography data of the Huangbai which obtained under the condition of standard test and also make the information reduction. Obtaining the great peaks of linear independent vectors and obtaining every clustering centre data of Huangbai by the fuzzy and Defuzzification methods. Make Huangbai criterion and sample data as weibull distribution to calculate similar. This research combines the plant morphology, chemistry, statistics and calculating technology to establish the pattern identification methods of quality and have good attempt to Chinese traditional machine quality methods. The research results provide the basis for quality standard revision of Huangbai.

Research on Medicine Industry and Manufacturing with North Schisandra Quality Assessment Based on Knowledge Reduction and Defuzzification Normal-Weibull Distribution

2014 ◽  
Vol 1014 ◽  
pp. 539-542
Author(s):  
Jian Yang Lin ◽  
Hui Zhou ◽  
Zhou Mi Kan
Keyword(s):  
Chinese Medicine ◽  
Weibull Distribution ◽  
Plant Morphology ◽  
Standard Test ◽  
Morphological Classification ◽  
Knowledge Reduction ◽  
Identification Methods ◽  
The North ◽  
Sample Data

According to the traditional morphological classification, the North Schisandra quality of traditional chinese medicine is divided into recommended products and non-recommended products; Discrete the chromatography data of the North Schisandra which obtained under the condition of standard test and also make the knowledge reduction. Obtaining the great peaks of linear independent vectors and obtaining every clustering centre data of North Schisandra by the fuzzy and Defuzzification methods. Make North Schisandra criterion and sample data as Normal-Weibull distribution to calculate similar. This research combines the plant morphology, chemistry, statistics and calculating technology to establish the pattern identification methods of quality and have good attempt to Chinese traditional machine quality methods. The research results provide the basis for medicine industry and manufacturing.

scholarly journals Calling for improved quality in the registration of traditional Chinese medicine during the public health emergency: a survey of trial registries for COVID-19, H1N1, and SARS

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhuoran Kuang ◽  
◽  
Xiaoyan Li ◽  
Jianxiong Cai ◽  
Yaolong Chen ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Secondary Outcome ◽  
Specific Information ◽  
Clinical Trial Registry ◽  
Data Set ◽  
Diagnosis Criteria

Abstract Objective To assess the registration quality of traditional Chinese medicine (TCM) clinical trials for COVID-19, H1N1, and SARS. Method We searched for clinical trial registrations of TCM in the WHO International Clinical Trials Registry Platform (ICTRP) and Chinese Clinical Trial Registry (ChiCTR) on April 30, 2020. The registration quality assessment is based on the WHO Trial Registration Data Set (Version 1.3.1) and extra items for TCM information, including TCM background, theoretical origin, specific diagnosis criteria, description of intervention, and outcomes. Results A total of 136 records were examined, including 129 severe acute respiratory syndrome coronavirus 2 (COVID-19) and 7 H1N1 influenza (H1N1) patients. The deficiencies in the registration of TCM clinical trials (CTs) mainly focus on a low percentage reporting detailed information about interventions (46.6%), primary outcome(s) (37.7%), and key secondary outcome(s) (18.4%) and a lack of summary result (0%). For the TCM items, none of the clinical trial registrations reported the TCM background and rationale; only 6.6% provided the TCM diagnosis criteria or a description of the TCM intervention; and 27.9% provided TCM outcome(s). Conclusion Overall, although the number of registrations of TCM CTs increased, the registration quality was low. The registration quality of TCM CTs should be improved by more detailed reporting of interventions and outcomes, TCM-specific information, and sharing of the result data.

Bibliometric Study on the Highly Cited Papers and Correlation Between Citation Frequency and Download Frequency in Chinese Medicine Journals

2021 ◽  
pp. 2153004
Author(s):  
Qinghui Qu ◽  
Xinyang Zhang
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Academic Quality ◽  
Academic Journal ◽  
Research Papers ◽  
Highly Cited Papers ◽  
Natural Medicine ◽  
Citation Frequency ◽  
Highly Cited

The purpose of this paper is to retrieve and study the highly cited papers as well as the correlation between the citation frequency and the download frequency of the 20 traditional Chinese medicine journals in China, in order to provide the guidance for improving the influence and academic quality of these journals. Bibliometric analyses were conducted on 1103 papers of 20 traditional Chinese medicine journals from 2011 to 2020 by retrieving for the China Academic Journal Network Publishing Database (CAJD) in China National Knowledge Infrastructure (CNKI). SPSS 17.0 software was used to analyze the correlation between the citation frequency and the download frequency via conducting regression fitting and establishing the mathematical models. The results showed that the total citations of the 1103 papers were 93051 times and the average citations were 84.36 times per paper. The total downloads of the 1103 papers were 2058442 times, and the average downloads were 1866.22 times per paper. China Journal of Chinese Materia Medica ranked first according to the number of papers, total citations and total downloads. The citations of Journal of Chinese Medicinal Materials ranked first based on the number of citations per paper. One of Li’s paper had been cited the most (983 times). There were 629 (57.03%) papers whose first author was from universities. The scopes of the first authors were distributed in 29 regions and 2 special administrative regions (Macao, Hong Kong) in China. The authors from Beijing published 283 (25.66%) papers, ranking number one. The number of papers supported by funds was 882 (79.96%). The research results of correlation showed that the citation frequency and the download frequency of the highly cited papers had a highly positive correlation from both journal and paper level for whether the sample data of journals was normally distributed or nonnormally distributed. The correlation coefficients of the 20 journals at journal level and that at paper level were 0.9765 and 0.6677, respectively. The correlation was better at journal level than that at paper level, while the optimal regression fitting was all cubic polynomial. Among the 1103 papers, there were 684 (62.01%) research papers and 419 (37.99%) review papers. The main citation period of the top 15 papers was from the 2nd year to the 6th year after publication, accounting for 78.39%. Papers on clinical therapeutics research, papers on the pharmacological effects and its mechanism of traditional Chinese medicine, and papers on traditional Chinese medicine and natural medicine were the main source of the highly cited papers of the traditional Chinese medicine journals. Editors of the journals should focus on the above-mentioned research areas to select manuscripts for exploiting the excellent sources extensively, while paying attention to review papers, focusing on national major or key projects, paying attention to network spreading, stabilizing authors with quality services, in order to improve the influence and the academic quality of journals.

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