Evaluations of AI Applications in Healthcare
Description
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.
You will 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
Tuition:
This course is part of the AI in Healthcare Specialization and part of a monthly subscription of $79.
Dates and Duration
Original Release Date: 09/10/2020
Expiration Date: 09/10/2023
Estimated Time to Complete: 9 hours and 30 minutes
CME Credits Offered: 9.50
Accreditation
The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.
The Stanford University School of Medicine designates this enduring material for a maximum of 9.50 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Disclosures
The Stanford University School of Medicine adheres to ACCME Criteria, Standards and Policies regarding industry support of continuing medical education. There are no relevant financial relationships with ACCME-defined commercial interests for anyone who was in control of the content of this activity.
