This course teaches you the fundamentals of transforming clinical practice using predictive models. This course examines specific challenges and methods of clinical implementation, that clinical data scientists must be aware of when developing their predictive models.
Predictive Modeling and Transforming Clinical Practice
This course is part of Clinical Data Science Specialization
Instructor: Laura K. Wiley, PhD
Sponsored by UNAM
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There are 5 modules in this course
Learn about the many types of clinical prediction models that exist and how they are put into practice.
What's included
8 videos4 readings1 assignment
Understand how qualitative methods can be used to develop clinical prediction models that are more likely to transform clinical practice.
What's included
9 videos1 assignment1 peer review
Learn about the different tools that are used to implement clinical prediction models in practice and the factors that affect implementations over time.
What's included
5 videos1 assignment
Understand how the different types of clinical data can be used in prediction models and learn how choices made during model construction affect the utility of the model in practice.
What's included
8 videos2 readings2 assignments
Put your new skills to the test - develop a clinical prediction model to asses risk of death during a stay in an Intensive Care Unit (ICU) stay.
What's included
1 video1 peer review
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