Predictive Modeling and Transforming Clinical Practice
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Approx. 11 hours to complete
Course Summary
This course teaches clinical predictive modeling, a field that combines clinical knowledge with statistical modeling to improve patient outcomes. Students will learn to develop and evaluate predictive models using real-world clinical data.Key Learning Points
- Learn to develop and evaluate predictive models using real-world clinical data
- Combine clinical knowledge with statistical modeling to improve patient outcomes
- Understand the importance of data quality and feature selection in predictive modeling
Related Topics for further study
Learning Outcomes
- Understand the basics of clinical predictive modeling
- Learn how to develop and evaluate predictive models using real-world clinical data
- Apply clinical knowledge and statistical modeling to improve patient outcomes
Prerequisites or good to have knowledge before taking this course
- Basic understanding of statistics
- Familiarity with clinical terminology
- Access to a computer with internet connection
Course Difficulty Level
IntermediateCourse Format
- Online self-paced course
- Video lectures
- Quizzes and assignments
Similar Courses
- Healthcare Analytics: Regression in R
- Data Science in Healthcare
- Clinical Data Science
Related Education Paths
- Certificate in Clinical Data Management
- Certificate in Biostatistics
- Master of Science in Health Informatics
Notable People in This Field
- Cardiologist and Author
- Surgeon and Author
Related Books
Description
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.
Outline
- Introduction: Clinical Prediction Models
- Welcome to Predictive Modeling and Transforming Clinical Practice
- Setting Expectations
- Introduction to Clinical Prediction Models
- Types of Clinical Prediction Models
- Clinical Prediction Models
- Operational Prediction Models
- Financial Prediction Models
- Developing Clinical Prediction Models
- Introduction to Specialization Instructors
- Course Policies
- Accessing Course Data and Technology Platform
- Week 1 Assessment
- Tools: Ensuring Model Usability
- Ensuring Model Usability
- Introduction to Qualitative Methods
- Qualitative Methods: Choosing the Right Tool
- Qualitative Methods: Population Selection
- Qualitative Methods: Data Collection
- Qualitative Methods: Data Analysis
- Qualitative Methods for Transforming Clinical Practice
- Introduction to Workflow Observations
- Qualitative Project Introduction
- Week 2 Assessment
- Techniques: Model Implementation and Sustainability
- Introduction to Clinical Prediction Model Implementation and Sustainability
- Methods of Changing Clinical Practice
- Fundamentals of Clinical Decision Support
- Clinical Decision Support for Prediction Models
- Sustainability of Clinical Prediction Models
- Week 3 Assessment
- Techniques: Data Selection, Model Building, and Evaluation
- Building Prediction Models
- Clinical Data for Prediction Models
- Clinical Prediction Models: Encounters
- Clinical Prediction Models: Billing Data
- Clinical Prediction Models: Laboratory Data
- Clinical Prediction Models: Medications
- Clinical Prediction Models: Clinical Observations
- Clinical Prediction Models: Demographics, Health, Social, & Family History
- Building a Clinical Prediction Model
- Note about the Assessment
- Building a Clinical Prediction Model - Try it Out For Yourself Exercise
- Week 4 Assessment
- Practical Application: Developing a Clinical Prediction Model
- Welcome to Practical Applications!
Summary of User Reviews
Read reviews and ratings for Clinical Predictive Modeling from Coursera. Users have praised the course for its practical approach towards modeling and its relevance in real-world scenarios.Key Aspect Users Liked About This Course
The course has a practical approach towards modeling and its relevance in real-world scenarios was highly appreciated by many users.Pros from User Reviews
- Great practical examples and assignments
- Relevant and applicable to real-world scenarios
- In-depth content with clear explanations
Cons from User Reviews
- Some users found the course to be too basic
- Lack of interaction with instructors and peers
- Some users felt that the course was too time-consuming
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