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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- 5 stars69.69%
- 4 stars18.18%
- 3 stars3.03%
- 1 star9.09%
來自IDENTIFYING PATIENT POPULATIONS的熱門評論
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 course, gives a solid understanding of computational phenotyping. Also teaches some R programming!
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.
This is a well-presented course. I highly recommend.
關於 Clinical Data Science 專項課程
Are you interested in how to use data generated by doctors, nurses, and the healthcare system to improve the care of future patients? If so, you may be a future clinical data scientist!
I live in an area that restricts access to Google products. Will I be able to complete the specialization?