Stakeholder Workshops
Second Stakeholder Workshop
The exponential increase in healthcare data, as well as the fast-paced technology developments, have resulted in promising novel AI systems for disease detection and risk prediction. However, the adoption of AI in clinical settings remains limited, mostly due to the limited data quality and interoperability across heterogeneous clinical centres and electronic health records, the absence of robust validation procedures, and the distrust of predictions and decisions generated by AI systems. Starting from the experience of the European Metrology Partnership Project 22HLT05 MAIBAI, this workshop aims at discussing the main strategies that can be adopted to face the above issues, with the design of a standardised and impartial framework for performance, generalisability and suitability assessment of AI systems in the clinical domain. Special attention will also be devoted to the development of large-scale and high-quality medical databases, the investigation of real-world data and the key standards relevant to AI-enabled medical devices.
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