Identifying Patient Populations

所在平台: CourseraArchive

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大学或机构: CourseraNew

课程主页: https://www.coursera.org/archive/computational-phenotyping

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课程大纲

Introduction: Identifying Patient Populations
Tools: Clinical Data Types
Techniques: Data Manipulations and Combinations
Techniques: Algorithm Selection and Portability

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This course teaches you the fundamentals of computational phenotyping, a biomedical informatics method for identifying patient populations. In this course you will learn how different clinical data types perform when trying to identify patients with a particular disease or trait. You will also learn how to program different data manipulations and combinations to increase the complexity and improve the performance of your algorithms. Finally, you will have a chance to put your skills to the test with a real-world practical application where you develop a computational phenotyping algorithm to identify patients who have hypertension. You will complete this work using a real clinical data set while using a free, online computational environment for data science hosted by our Industry Partner Google Cloud.

识别患者人群:本课程教您计算表型的基本知识,这是一种用于识别患者人群的生物医学信息学方法。在本课程中,您将学习在尝试识别具有特定疾病或特征的患者时不同临床数据类型的表现。您还将学习如何对不同的数据操作和组合进行编程,以增加复杂性并提高算法性能。最后,您将有机会通过实际应用来测试您的技能,在实际应用中,您将开发出计算表型算法来识别患有高血压的患者。您将使用真实的临床数据集来完成这项工作,同时使用由我们的行业合作伙伴Google Cloud托管的免费在线计算机科学计算环境。

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