University of Colorado System

Identifying Patient Populations

Laura K. Wiley, PhD

Instructor: Laura K. Wiley, PhD

3,472 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.5

(39 reviews)

Intermediate level

Recommended experience

13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.5

(39 reviews)

Intermediate level

Recommended experience

13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • 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.

Details to know

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Assessments

7 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Clinical Data Science Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 5 modules in this course

Learn about computational phenotyping and how to use the technique to identify patient populations.

What's included

5 videos10 readings2 assignments

Understand how different clinical data types can be used to identify patient populations. Begin developing a computational phenotyping algorithm to identify patients with type II diabetes.

What's included

5 videos2 readings2 assignments

Learn how to manipulate individual data types and combine multiple data types in computational phenotyping algorithms. Develop a more sophisticated computational phenotyping algorithm to identify patients with type II diabetes.

What's included

2 videos2 readings2 assignments

Understand how to select a single "best" computational phenotyping algorithm. Finalize and justify a phenotyping algorithm for type II diabetes.

What's included

1 video1 reading1 assignment

Put your new skills to the test - develop an computational phenotyping algorithm to identify patients with hypertension.

What's included

1 reading1 peer review

Instructor

Instructor ratings
4.7 (7 ratings)
Laura K. Wiley, PhD
University of Colorado System
6 Courses29,502 learners

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Recommended if you're interested in Data Analysis

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Learner reviews

4.5

39 reviews

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Showing 3 of 39

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5

Reviewed on May 12, 2019

WH
4

Reviewed on Apr 4, 2019

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4

Reviewed on Dec 12, 2019

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