Machine Learning in Radiology – Forum, July 15 2022

1000 563 MaLMIC - Machine Learning in Medical Imaging Consortium

Join the Machine Learning in Medical Imaging Consortium (MaLMIC) for an opportunity to network

Machine Learning in Radiology

Friday, July 15, 2022
3:30 to 5:30 p.m. ET

Jaron Chong will start the forum with an overview of the state of AI for medical imaging in Canada. The second presentation will be by Alex Bilbily talking about the road to building impactful AI medical devices. The third presentation will be by Benjamin Fine on pre-deployment evaluation. The three talks will be followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Interested in joining? Please contact us.

Machine Learning in Radiology

Friday, July 15, 2022
3:30 to 5:30 p.m. ET

Jaron Chong will start the forum with an overview of the state of AI for medical imaging in Canada. The second presentation will be by Alex Bilbily talking about the road to building impactful AI medical devices. The third presentation will be by Benjamin Fine on pre-deployment evaluation. The three talks will be followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Interested in joining? Please contact us.

A Test Is Not Enough: Information Leaks, Generalization Failures, and the Need for Validation

Jaron Chong, MD
Radiologist, London Health Sciences Centre

Talk summary: Current generation radiology AI models pose unique challenges and risks during implementation to full clinical practice. Jaron will review new pathways and requirements from Health Canada for medical AI applications, examples of information leaks and contributors to generalization failures, and the urgent need for AI trial registration and better model validation.

The Road to Building Impactful AI Medical Devices

Alexander Bilbily, MD
Co-CEO & Co-Founder, 16 Bit Inc.

Talk summary: Alexander will talk about the full lifecycle of a medical AI tool and the critical questions to ask at each phase. The phases include idea inception, algorithm development, clinical validation, product development, regulatory approval, and reimbursement.