Introduction to AI-integrated Medical Devices Regulatory Compliance
Online Course Course

Introduction to AI-integrated Medical Devices Regulatory Compliance

  • Dates 31 January 2024
  • Location Zoom
  • Hours 5 hours
  • Language English
  • Hours 14:00-19:00 Brussels
  • 13:00-18:00 UK
  • 08:00am-01:00pm New York
$900 Until 31 Jan 2024
About the Course
Ady Banin
Lecturer: Ady Banin
Ady Banin is a regulatory and quality professional in the field of medical devices with over 17 years of practical experience in leading companies in successfully meeting regulatory requirements. Ady has diverse experience with various devices, from implanted products (active and inactive) to products that use software and artificial intelligence. Ady is detail-oriented, with high analytical capabilities and a love for data analysis; has a practical, hands-on approach and creative thinking that helps solve complex situations; and a passion for learning and teaching.
Ady’s expertise includes (non-exhaustive list):
• Setting up quality systems from scratch and managing them, including continual improvement and regulatory compliance
• Customized training, tailored to the learners’ needs
• Risk manageme

This introductory course provides a comprehensive overview of the regulatory landscape governing AI-integrated medical devices.

Participants will gain insights into the unique considerations and challenges of bringing these innovative technologies to market. Covering key topics from algorithm validation to ethical considerations, this course equips attendees with foundational knowledge crucial for navigating the regulatory pathway.

The course will also cover the most up-to-date standards and guidance related to AI-integrated medical devices.


  1. Introduction to AI-Based Medical Devices- unique features and challenges
  2. Regulatory Framework for AI-Based Medical Devices
  3. Algorithm Training, Validation, and Interpretability
  4. Data Quality, Integrity, and Risks Related to AI
  5. Pre-market Regulatory Processes (including QMS considerations, design planning and validation, etc.)
  6. Clinical Trials for AI-Based Medical Devices
  7. Post-market Surveillance and Continuous Improvement
  8. Ethical Considerations and Bias Mitigation
  9. Data Privacy, Security, and Standards
  10. Case Studies

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