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Application of Data Mining to Zheng Studies of Chinese Medicine based on CER

机译:基于CER的数据挖掘对郑郑研究的应用

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Comparative effectiveness research (CER) is a new clinical study model featured by its strategic framework consists of four categories and three themes. The core strategy of CER is to conduct observational longitude research supported by electronic registry and large database based on real world practice. Since CER studies do not uses a classic randomized control trial (RCT) design, the well-developed data analytic methods for RCTs are challenged. The data groups which are not acquired from the same time point, or have significant difference at the baseline are unable to be compared by the classic differential statistical methods, or the outcome will be without robust statistical support. In this paper, we described the characteristics of the Zheng studies of Chinese medicine. Then some data analytic methods based on machine learning are introduced as potential solutions for the data processing in the CER research of Chinese medicine. Finally, a new strategic framework is introduced to establish the CER methodology for Chinese medicine.
机译:比较有效性研究(CER)是其战略框架特色的新临床研究模式,包括四个类别和三个主题。 CER的核心战略是通过基于现实世界实践的电子登记处和大型数据库支持的观察经度研究。由于CER研究不使用经典的随机控制试验(RCT)设计,因此RCT的良好的数据分析方法受到挑战。未在同一时间点获取的数据组,或者在基线上具有显着差异,无法通过经典的差异统计方法进行比较,或者结果将在没有稳健的统计支持的情况下进行比较。在本文中,我们描述了中医郑研究的特征。然后,基于机器学习的一些数据分析方法被引入了中医药CER研究中数据处理的潜在解决方案。最后,介绍了一种新的战略框架,以建立中药的CER方法。

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