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.
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このコースについて
Some programming experience in any language.
貴社では、従業員に需要のあるスキルを訓練させることによって利益を得ることができるでしょうか?
Coursera for Businessを試す学習内容
Create a computational phenotyping algorithm
Assess algorithm performance in the context of analytic goal.
Create combinations of at least three data types using boolean logic
Explain the impact of individual data type performance on computational phenotyping.
Some programming experience in any language.
貴社では、従業員に需要のあるスキルを訓練させることによって利益を得ることができるでしょうか?
Coursera for Businessを試すシラバス - 本コースの学習内容
Introduction: Identifying Patient Populations
Tools: Clinical Data Types
Techniques: Data Manipulations and Combinations
Techniques: Algorithm Selection and Portability
レビュー
- 5 stars71.42%
- 4 stars17.14%
- 3 stars2.85%
- 1 star8.57%
IDENTIFYING PATIENT POPULATIONS からの人気レビュー
This is a well-presented course. I highly recommend.
The instructor does a great job of providing hands-on teaching in addition to lecture. However, this course required a lot of knowledge of R, which wasn't provided in the introductory course.
Great overview of how to identify Patient Population and the in and out of what to look for when you are thinking about your potential research project will involve.
Clinical Data Science専門講座について

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