Apply AI: Piloting AI-based image screening in medical centres

Expected Impact

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Expected Outcome

Outcomes and deliverables

• One or more proofs-of-concept of replicable, scalable cloud-based AI/GenAI systems for analysis of medical imaging data in a healthcare setting, with demonstration of the role of the clinicians in validating AI/GenAI findings and reports showcasing seamless integration of the system into clinical workflows.
• Evidence-based analysis of (cost-)efficiency of the piloted solutions for healthcare systems for regulatory and HTA purposes.
• Two or more events or workshops organised per year and per project for the European network of AI-powered advanced screening centres. The agenda should include lessons learned from the project activities, as well as other items relevant to the network. Participant satisfaction rates should be measured for the events and workshops.
• Medical centres in the consortium joined the European network of AI-powered advanced screening centres under the Apply AI Strategy.
• A plan for obtaining regulatory approval for application of the AI/GenAI solutions in real life scenarios and clinical settings. This includes the required risk management and compliance activities, as well as clinical evaluation plans and post-market clinical follow-up.
• Detailed data protection and cybersecurity plan, with measures to secure sensitive health data, mitigate cybersecurity risks, and comply with EU legal and ethical frameworks.
• Sustainability plan for the uptake of the systems across the EU.
• Stakeholder engagement and dissemination report with measurable actions (KPIs).

Scope

Each project awarded in this action should implement a scalable cloud-based AI/GenAI system running European trustworthy and safe AI/GenAI algorithms that were developed, trained and validated using very large sets of patient data. They should put in place a secure, privacy-preserving cloud environment required for the health data analysis tasks, with appropriate access and identification tools for authorised use only, and implement the whole system as described under this topic, seamlessly integrated in regular clinical workflows of the care settings involved. Interoperability and the need to communicate with the health IT infrastructure (e.g. the electronic health record (EHR) of the patient, Picture archiving and communication systems (PACS), Radiological Information Systems (RIS), etc.) need to be addressed.

The projects should demonstrate the integration and large-scale validation of cloud-based AI/GenAI systems, following a thorough assessment and testing over a large number of patient test cases in real healthcare settings. The proposers are expected to choose the types of health data, the AI/GenAI algorithms that are trustworthy and secure, and the medical use cases, with the focus disease areas being cancer and cardiovascular. The projects should perform technical and clinical validation of the systems, generating evidence on AI systems’ performance and usability in different clinical settings. They shall use the AI systems for screening in clinical settings, perform local performance evaluation and post-deployment monitoring of the solutions, including evidence generation on cost-efficiency in view of regulatory requirements and health technology assessment (HTA). Whenever relevant, each project should deploy AI/GenAI solutions already tested and validated within the TEF for Health.