AI implementation in clinical practice

Hidden challenges and the hidden technical debt

Over the last 8 years, there have been tremendous advances in developing AI models for pathology, either focused on specific tasks or taking on complete diagnostic workflows. These models have achieved performance equivalent to the pathologist, but the uptake has been quite slow in clinical practice.

In this session, we examine the technical challenges and the hidden technical debt associated with implementing AI in clinical practice, while identifying the pitfalls that can threaten the success of such an undertaking. 

Nikolas Stathonikos, Manager AI development & implementation, has been leading the IT department of the pathology department at the University Medical Center Utrecht since 2011 as a resident expert on digital pathology. As a PhD candidate in “Digital pathology and AI implementation”, he has taken the role of implementing AI in clinical practice. 

This webinar was arranged in conjunction with the 7th Digital Pathology & AI Congress Europe on December 3, 2020.

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