数字中医药（英文）2018，Vol.1Issue(2)：143-154,12.
关于辨证的微信学习平台的建设
Design of a WeChat Learning Platform for Syndrome Differentiation
摘要
Abstract
Objective To design a WeChat mini program called Chinese Syndrome Differentiation Learning Platform (CSDLP) on smartphone to improve health literacy. Methods The developer tools of WeChat (Version:v1.01.170925) were used for designing and debugging the mini program. SPSS17.0 was used for statistical purposes. "View container""Basic content""Form component""Navigation" and"Media components" were used for the development of the WeChat mini program. The detailed method was referred to https://mp.weixin.qq.com/debug/wxadoc/dev/. Results A WeChat mini program called CSDLP was developed. This program has three major functions which are WeChat reading, WeChat class and WeChat syndrome differentiation. The official test report showed that there were no functionality errors for the seven android smartphones (referred to as A, B, C, D, E, F and G) that CSDLP was tested on. Statistical analysis results showed that the average memory in D, E, F and G was lower than in A, B and C. Average ratio was the highest in F and the lowest in G. The average loading time was the same for all smartphones. The audio database for diagnostics using traditional Chinese medicine (TCM) and a lecture video database were based on diagnostic textbook. Our team built a syndrome differentiation database which included 51 diseases. Conclusion CSDLP can improve knowledge visualization, studying process, and information sharing in terms of the training and development of new techniques for syndrome differentiation and treatment in TCM, and it can provide a better illustration for people to understand TCM.关键词
辨证论治/学习平台/智能手机/微信程序Key words
Syndrome differentiation and treatment/Learning platform/Smartphone/WeChat Program引用本文复制引用
邓文祥,朱建平,刘应蛟,张弋戈,黄惠勇,张文安..关于辨证的微信学习平台的建设[J].数字中医药（英文）,2018,1(2):143-154,12.基金项目
We thank for the funding support from the National Natural Science Foundation of China (No. 81373551) and 2016 Hunan Provincial Postgraduate Research Innovation Project (No. CX2016B367). （No. 81373551）
