On May 22nd, from 10:30 to 11:30 CEST, a session titled “AISYM4MED Platform: Supporting the Development of Compliant AI for Health” presented the design approach and objectives behind the AISYM4MED platform.
The session covered key aspects considered in the platform’s development, including privacy protection, data quality, data accessibility, and the support for machine learning model development in the healthcare domain. The platform is designed to facilitate access to a trustworthy health data ecosystem, integrating data synthesis and auditing tools to assist machine learning engineers and AI developers in building compliant and reliable AI systems for medical use.
Speakers shared the technical and regulatory challenges the AISYM4MED consortium is addressing, and demonstrate the platform’s capabilities. The session will also open a discussion with attendees to exchange insights on needs, challenges, and expectations related to developing AI systems in healthcare.
This session offers a detailed look at current efforts to support compliance-aware AI development in medicine and the collaborative work being done to improve data infrastructure in health AI.
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