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
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Beginner level
No prior experience required
1 week to complete
at 10 hours a week
Flexible schedule
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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
Skills you'll gain
- Healthcare Ethics
- Clinical Informatics
- Data Quality
- Health Equity
- Clinical Research Ethics
- Precision Medicine
- Continuous Monitoring
- Data Ethics
- Predictive Modeling
- Application Deployment
- Regulatory Compliance
- Health Technology
- Health Disparities
- AI Integrations
- Decision Support Systems
- Responsible AI
- Clinical Assessment
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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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