Introduction to Use Cases
The integration of AI-driven medical devices into healthcare requires addressing the challenges and complexities that arise throughout their development, testing, and deployment. Ensuring the successful implementation of these solutions demands rigorous evaluation in realistic clinical settings. This initiative adopts a hands-on approach, implementing three carefully selected use cases that span different phases of the medical device lifecycle: development, testing, and deployment.
A key focus is leveraging HDAB infrastructures across multiple European nations to facilitate access to high-quality, real-world datasets essential for AI model development, validation, and deployment. This initiative tackles critical healthcare challenges, from predictive modeling for chronic diseases to AI-assisted imaging evaluation and real-world validation of digital health solutions. Seamless coordination with technical research efforts ensures that insights from development translate into practical applications while real-world findings refine earlier AI medical device stages, maximizing scalability and impact within healthcare.
By addressing these core objectives, WP5 seeks to bridge the gap between AI research and its real-world implementation in healthcare. The findings from these use cases will not only refine AI-based medical devices but also inform regulatory pathways, improve clinical decision-making, and ultimately enhance patient outcomes across Europe.
Facilitate Knowledge Sharing: Establish a structured framework for cross-team collaboration and best practices to enhance AI-based medical device integration.
Advance AI in Chronic Kidney Disease: Develop a predictive AI model using nationwide health data from three countries to improve early detection and risk stratification.
Enhance AI-Assisted Cancer Detection: Implement a standardized evaluation methodology with real-world validation using lung scanner images and mammograms to assess AI-driven oncology solutions.
Validate AI in Cardiac Monitoring: Utilize large-scale health datasets to assess a remote monitoring solution for cardiac implants, supporting clinical validation and reimbursement pathways in France and Germany.