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Identifying Patient Populations
  • Level Professional
  • Duration 13 hours
  • Course by University of Colorado System
  • Offered by

About

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.

Modules

Welcome to Identifying Patient Populations

    • 1 Videos
    • 1 Readings
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1 Videos

  • Welcome to Identifying Patient Populations

1 Readings

  • Get help and meet other learners in this course. Join your discussion forums!

Getting Started

    • 3 Readings
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3 Readings

  • Introduction to Specialization Instructors
  • Course Policies
  • Accessing Course Data and Technology Platform

Introduction to Computational Phenotyping

    • 1 Videos
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1 Videos

  • Introduction to Computational Phenotyping

Manual Record Review

    • 3 Videos
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3 Videos

  • Introduction to Manual Record Review
  • Manual Record Review: Selecting Reviewers and Records
  • Manual Record Review: Tools and Techniques

Introduction to Course Example

    • 1 Readings
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1 Readings

  • Introduction to Course Example

Additional Resources (Optional)

    • 5 Readings
    • 1 Assignment
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1 Assignment

  • Week 1 Practice Quiz

5 Readings

  • Introduction to Manual Record Review
  • Methods - Selecting Reviewers
  • Methods - Selecting Records for Review
  • Methods - Creating Review Instruments and Protocols
  • Methods - Assessing Review Quality

Week 1 Assessment

    • 1 Assignment
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1 Assignment

  • Week 1 Assessment

Data Types for Computational Phenotyping

    • 5 Videos
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5 Videos

  • Data Types for Computational Phenotyping
  • Computational Phenotyping: Billing Data
  • Computational Phenotyping: Laboratory Data
  • Computational Phenotyping: Clinical Observations
  • Computational Phenotyping: Medications

Programming Examples and Exercises

    • 1 Readings
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1 Readings

  • Testing Individual Data Types

Additional Resources (Optional)

    • 1 Assignment
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1 Assignment

  • Programming Exercises Practice Quiz

Week 2 Assessment

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Week 2 Assessment

1 Readings

  • Note about the Assessment

Manipulating Individual Data Types

    • 1 Videos
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1 Videos

  • Manipulating Individual Data Types

Combining Multiple Data Types

    • 1 Videos
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1 Videos

  • Combining Multiple Data Types

Programming Examples and Exercises

    • 2 Readings
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2 Readings

  • Data Manipulations
  • Data Combinations

Additional Resources (Optional)

    • 1 Assignment
Show info about module content

1 Assignment

  • Programming Exercises Practice Quiz

Week 3 Assessment

    • 1 Assignment
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1 Assignment

  • Week 3 Assessment

Algorithm Selection and Portability

    • 1 Videos
    • 1 Readings
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1 Videos

  • Selecting a Final Algorithm

1 Readings

  • Assessing Algorithmic Accuracy, Complexity, and Portability

Week 4 Assessment

    • 1 Assignment
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1 Assignment

  • Week 4 Assessment

Welcome to Practical Applications!

    • 1 Readings
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1 Readings

  • Welcome to Practical Applications!

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

    • 1 PeerReview
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1 Peer Review

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

Auto Summary

Discover the essentials of computational phenotyping with the "Identifying Patient Populations" course, designed for professionals in the Data Science & AI domain. Led by Coursera, this comprehensive program delves into the biomedical informatics techniques essential for identifying specific patient groups based on various diseases or traits. Throughout the course, you'll explore the performance of different clinical data types and learn to enhance your algorithms through advanced data manipulations and combinations. Engage in hands-on learning by creating a computational phenotyping algorithm aimed at identifying patients with hypertension, utilizing a real clinical data set. Benefit from practical experience using a free, online computational environment provided by Google Cloud, Coursera's industry partner. Spanning 780 minutes, this professional-level course offers a robust curriculum tailored for those seeking to advance their expertise in data science applications within the healthcare sector. Enroll through the Starter subscription to begin your journey in transforming raw clinical data into actionable insights. Ideal for data scientists, healthcare informatics professionals, and anyone interested in the intersection of data science and medicine.

Laura K. Wiley, PhD
Instructor

Laura K. Wiley, PhD