With artificial intelligence applications proliferating throughout the healthcare system, stakeholders are faced with both opportunities and challenges of these evolving technologies. This course explores the principles of AI deployment in healthcare and the framework used to evaluate downstream effects of AI healthcare solutions.
Evaluations of AI Applications in Healthcare
Evaluations of AI Applications in Healthcare
This course is part of AI in Healthcare Specialization
Instructors: Tina Hernandez-Boussard
Sponsored by Stanford University
15,913 already enrolled
Gain insight into a topic and learn the fundamentals.
4.5
(248 reviews)
Beginner level
No prior experience required
Flexible schedule
Approx. 11 hours
Learn at your own pace
94%
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What you'll learn
Principles and practical considerations for integrating AI into clinical workflows
Best practices of AI applications to promote fair and equitable healthcare solutions
Challenges of regulation of AI applications and which components of a model can be regulated
What standard evaluation metrics do and do not provide
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Assessments
22 assignments
Taught in English
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This course is part of the AI in Healthcare Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 8 modules in this course
What's included
10 videos2 readings3 assignments
What's included
15 videos2 readings4 assignments
What's included
19 videos2 readings5 assignments
What's included
18 videos2 readings5 assignments
What's included
18 videos2 readings4 assignments
Readings related to best ethical practices for AI in health care
What's included
3 readings
What's included
9 videos
What's included
3 readings1 assignment
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4.5 (79 ratings)Offered by
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