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Learner Reviews & Feedback for Identifying Patient Populations by University of Colorado System

4.5
17 ratings
•
6 reviews

About the Course

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....

Top reviews

QQ

Jun 20, 2019

excellent course.\n\nThe first MOOC on computational pheonotying

AB

May 13, 2019

This is a well-presented course. I highly recommend.

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1 - 6 of 6 Reviews for Identifying Patient Populations

By Angela B

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May 13, 2019

This is a well-presented course. I highly recommend.

By qianmengxiao

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Jun 20, 2019

excellent course.

The first MOOC on computational pheonotying

By Mor K

•

Jul 22, 2019

Great course, gives a solid understanding of computational phenotyping. Also teaches some R programming!

By William H

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Apr 05, 2019

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.

By rroddema

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Sep 20, 2019

I am simply not able to finish the course because no peer reviewers available.

Not sure who is responsible but as a student I do not care.

Please stop asking money when you cannot deliver.

Course content is very good.

By Vu T T T

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Sep 16, 2019

A good course on identifying patient populations with R. However, some concepts/use of functions in R programming do not get fully-explained and needs learnt from other sources.

Courses 4, 5 and 6 are not available so cannot complete the entire specialization.