Evaluations of AI Applications in Healthcare

Evaluations of AI Applications in Healthcare

What you will learn from the Evaluations of AI Applications in Healthcare

  • 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
  • Standard evaluation metrics do and do not provide
  • Why AI is needed in Healthcare and Growth of AI in Healthcare
  • Care Integration, Clinical Integration & Technical Integration, Considerations
  • Types of Bias (Historical Bias, Representation Bias, Measurement Bias, Aggregation Bias, Evaluation Bias, Deployment Bias)
  • Identifying & Mitigating Conflicts of Interest

Course Instructors Tina Hernandez-Boussard, Mildred Cho & Offered by Stanford University from Coursera

Course Duration: 11 hours to complete

Course is for Beginner Level

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