Registration
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Description
Particularly when using AI-based systems in healthcare, it is important that these medical devices are safe and effective. The quality of AI-based systems depends largely on the data used to train the AI model and that used in subsequent operation. Known challenges for data regarding AI model development include:
sufficient data set size,
consistency between and within data sets,
completeness,
representativeness, and
absence of bias.
For manufacturers, the question arises how they can implement data management efficiently and in compliance with legal requirements for both the development and market phases of the AI-based medical device. In addition, manufacturers should take a close look at the actual conditions at the users in the clinical environment.
This event will give you an overview of the requirements for data in AI-based medical devices, as well as insights into the technical implementation of data management and the application and challenges in clinical practice.
We are looing forward to your participation!
Agenda
 13:55 | Welcome and registration |
14:00 | Data for AI-based medical devices: regulatory challenges and how to address them Thorsten Prinz, VDE
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14:30 | Data for AI-based medical devices: technical challenges and how to address them Fabian Stieler, University of Augsburg
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15:00 | Summary and discussion |
15:15 | End of the event |
Preliminary program. Subject to changes / adjustments
The event is organized for at least 10 participants. If the minimum number of participants is not reached one week before the start of the event, we reserve the right to cancel it. For organizational reasons, registration for our events usually closes 3 days before the event date. Thank you for your understanding.