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
This course is part of AI in Healthcare Specialization
Instructors: Tina Hernandez-Boussard
Sponsored by Louisiana Workforce Commission
16,921 already enrolled
(262 reviews)
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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There are 8 modules in this course
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10 videos2 readings3 assignments
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15 videos2 readings4 assignments
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19 videos2 readings5 assignments
What's included
18 videos2 readings5 assignments
What's included
18 videos2 readings4 assignments
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Reviewed on Dec 11, 2024
V easy to follow. Could finish at my own pace. Always theory went hand in hand with real life examples which made it interesting.
Reviewed on Oct 16, 2020
Nicely Framed and Executed in a simple language so anyone can catch up earliest.
Reviewed on Jul 16, 2023
AI applications in Healthcare have to be xyz and we as medical students should know what those xyx values are and this course does that exactly.
Recommended if you're interested in Data Science
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