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Identifying Patient Populations

Master computational phenotyping techniques to identify and analyze patient populations using clinical data science.

Master computational phenotyping techniques to identify and analyze patient populations using clinical data science.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Clinical Data Science Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.5

(39 ratings)

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Identifying Patient Populations

This course includes

13 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Create and validate computational phenotyping algorithms

  • Analyze multiple clinical data types effectively

  • Develop complex boolean logic combinations

  • Assess algorithm performance and accuracy

  • Implement manual record review techniques

Skills you'll gain

Computational Phenotyping
Clinical Data Analysis
Patient Population Identification
Healthcare Analytics
Data Manipulation
Algorithm Development
Medical Records Review
Boolean Logic
Statistical Analysis
Clinical Research

This course includes:

1.2 Hours PreRecorded video

7 assignments

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

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There are 5 modules in this course

This comprehensive course teaches the fundamentals of computational phenotyping for identifying patient populations. Students learn to evaluate different clinical data types, develop algorithms, and assess their performance. Using Google Cloud's platform and real clinical datasets, learners gain practical experience in creating and validating phenotyping algorithms, with a special focus on identifying conditions like hypertension and diabetes. The course combines theoretical knowledge with hands-on programming exercises.

Introduction: Identifying Patient Populations

Module 1 · 2 Hours to complete

Tools: Clinical Data Types

Module 2 · 2 Hours to complete

Techniques: Data Manipulations and Combinations

Module 3 · 3 Hours to complete

Techniques: Algorithm Selection and Portability

Module 4 · 0 Hours to complete

Practical Application: Develop a Computational Phenotyping Algorithm to Identify Patients with Hypertension

Module 5 · 3 Hours to complete

Fee Structure

Instructor

Laura K. Wiley, PhD
Laura K. Wiley, PhD

4.2 rating

9 Reviews

29,596 Students

6 Courses

Innovator in Precision Medicine and Biomedical Informatics

Dr. Laura K. Wiley is an Associate Professor in the Department of Biomedical Informatics at the University of Colorado Anschutz Medical Campus, where she focuses on leveraging electronic health records (EHR) for precision medicine discovery and implementation. With a Ph.D. in Human Genetics from Vanderbilt University, Dr. Wiley has developed computational phenotyping algorithms for EHR-linked biobanks and explored precision dosing of medications like warfarin, particularly in African American populations. She serves as the Chief Data Scientist for Health Data Compass, a cloud-based research data warehouse that integrates data from multiple institutions to enhance clinical research capabilities. Dr. Wiley has been actively involved in various initiatives, including a NIH Cancer Moonshot-funded project aimed at creating comprehensive tobacco cessation services at the University of Colorado Cancer Center. Her contributions to the field are recognized through her leadership roles in the American Medical Informatics Association and her involvement in developing the Coursera Clinical Data Science Specialization, which educates students on clinical research informatics skills. Through her research and teaching, Dr. Wiley is dedicated to advancing the integration of data science in healthcare to improve patient outcomes and foster innovation in medical practices.

Identifying Patient Populations

This course includes

13 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.5 course rating

39 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.