这也是我想审慎地告诉大家的一点：有时候，将数据挖掘算法应用到数据集有可能会生成一个糟糕的模型。
That takes us to an important point that I wanted to secretly and slyly get across to everyone: Sometimes applying a data mining algorithm to your data will produce a bad model.
在AMDD的情况下，通过模型转换取代人工工作，将糟糕需求的影响繁殖给了应用程序代码。
In the case of AMDD, the effects of poor requirements are propagated to the application code by means of model transformations instead of manual human effort.
在我的经历中，医疗信息系统的根本问题在于一个极其糟糕的数据模型，证据就是以下这些观察结果。
The root of the problem I experienced with health information systems is a very bad data model. Evidence supporting my claim includes these observations.
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