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Apply AI: Piloting AI-based image screening in medical centres
Funding Program
Digital Europe
Call number
DIGITAL-2026-AI-PILOTING-10-SCREENING
deadlines
Opening
21.04.2026
Deadline
01.10.2026 17:00
Funding rate
50%
Call budget
€ 9,000,000.00
Estimated EU contribution per project
€ 4,500,000.00
Link to the call
Link to the submission
Call content
short description
The aim of this action is to pilot the deployment of cloud-based AI/GenAI systems with trained European AI/GenAI algorithms. The systems would assist resource-limited health care settings (e.g., lack of medical specialists or inadequate infrastructure) with performing analysis of medical imaging data they are acquiring while providing healthcare services in their sites using medical imaging devices such as MRI, CT, X-rays, PETs, ultrasound, etc.
Call objectives
AI and GenAI applied to medical data can bring efficiencies in care settings and improve patient outcomes while reducing costs. AI/GenAI algorithms offer a major tool for early detection and diagnosis of a large variety of medical conditions, supporting decision-making by medical staff. They may be used, for example, to perform the initial medical imaging and clinical data analysis quickly in widely distributed medical centres equipped with medical imaging devices and with limited availability of specialised staff, to support the detection of suspected disease cases requiring specialist follow-up. This approach holds great potential for reducing inequalities in access to care across regions, alleviating staff shortages, speeding up diagnosis and decision-making for all, including those living far from specialised facilities, and drastically reducing health and care costs. In spite of its promise, AI is currently not widely taken up in clinical practice due to, among others, insufficient evidence on clinical utility and cost-efficiency.
The aim is to pilot the deployment of cloud-based AI/GenAI systems with trained European AI/GenAI algorithms. The systems would assist resource-limited health care settings (e.g., lack of medical specialists or inadequate infrastructure) with performing analysis of medical imaging data they are acquiring while providing healthcare services in their sites using medical imaging devices such as MRI, CT, X-rays, PETs, ultrasound, etc. By analysing imaging data, the system should automatically detect findings of potential clinical significance for a given patient, including incidental findings. Additional clinical data of a patient may be used, if available, to support the analysis and prioritisation of the case. When an anomaly is suspected, the system would send the patient data and suspected finding(s) to a medical doctor having the appropriate expertise and the resources required for verifying and validating the AI/GenAI-based suspected finding, and eventually plan the next steps in patient care. In addition, the system would help prioritise cases locally within the medical centres.
The proposed AI-based solution will have the following clinical impacts:
- Improve the early detection and diagnosis of cancer and cardiovascular diseases.
- Enhance prioritisation of critical cases, enabling faster decision-making.
- Optimize resources in radiology departments, alleviating workload pressures.
- Support underserved regions by enabling remote, high-quality screening without requiring on-site specialists.
- Reduce diagnostic delays through integrated workflows with existing clinical systems (e.g., PACS, RIS, EHR).
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Expected effects and impacts
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 identification, authentication and access management tools for authorised and secure 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.
A key element of the piloted system solutions will be their scalability and replicability across various eligible countries and their health systems, enabling consistent and equitable digital service delivery. Any solutions should be compatible with national health systems across eligible countries to allow for easier replication across different contexts. The AI/GenAI system will prioritise interoperability, integrating seamlessly with existing tools such as PACS, RIS, and EHR systems to avoid disruptions in clinical workflows. In this respect, the projects should largely disseminate their activity across several eligible countries by showing how their operation can be replicable across eligible countries. Replication and large-scale deployment across eligible countries is then expected to take place through funding from national sources (such as structural and regional funds, national funds, private funds or other). To ensure a wide societal uptake and acceptance of the AI-based screening approach, the projects should bring together technical, medical and public health expertise and patient representatives and address the applicable ethical and legal implications. The projects will ensure that AI/GenAI results are systematically validated by qualified medical professionals to confirm findings, assess clinical relevance, and maintain patient safety. This approach is essential for building trust and ensuring alignment with medical workflows. Active involvement of medical practitioners is required to ensure acceptability and usability of the pilot and to check its results. Medical practitioners will be actively engaged throughout the process to assess AI performance, validate outputs, and integrate the system seamlessly into clinical practice. In addition, active multi-stakeholder engagement, communication activities and capacity building measures are expected. To ensure public trust, the AI/GenAI systems to use must align with EU values and rules, particularly in terms of data protection, cybersecurity and compliance with the EU AI Act.
The projects should leverage already existing medical imaging and health data infrastructures, such as the Cancer Image Europe platform and HealthData@EU infrastructure of the European Health Data Space, as well as tools, algorithms and facilities for any further training of the algorithms. Where applicable, they should support innovative initiatives related to cancer, cardiovascular diseases and other non-communicable diseases and build on the results of successful projects funded under Horizon 2020, Horizon Europe, the Digital Europe Programme, EU4Health, or other relevant Union initiatives supporting innovation, such as the Cancer Image Europe platform.
The AI/GenAI algorithms and cloud infrastructure/services necessary for the projects must be either provided by the consortia or by a provider from an eligible country. The consortia should ensure the availability of the data sets and the agreements for their intended use, taking into account the relevant regulatory requirements.
The projects must involve medical centres from multiple eligible countries. The medical centres participating in the projects under this action should join and contribute to the European network of AI-powered advanced screening centres, to be established by the European Commission under the Apply AI Strategy.
The network will leverage the strong collaboration within the European Cancer Imaging Initiative and other relevant actions under the DIGITAL and EU4Health programmes, in particular the Cardiovascular Flagship under EU4Health WP 2025. It will initially focus on cancer and cardiovascular diseases. The projects under this action should reserve a budget for the purpose of organising and participating in network activities and regular exchanges among the network members.
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Expected results
- 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).
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Eligibility Criteria
Regions / countries for funding
Iceland (Ísland), Liechtenstein, Norway (Norge), Switzerland (Schweiz/Suisse/Svizzera)
eligible entities
Education and training institution, Non-Profit Organisation (NPO) / Non-Governmental Organisation (NGO), Other, Private institution, incl. private company (private for profit), Public Body (national, regional and local; incl. EGTCs), Research Institution incl. University, Small and medium-sized enterprise (SME)
Mandatory partnership
Yes
Project Partnership
In order to be eligible, the applicants (beneficiaries and affiliated entities) must:
- be legal entities (public or private bodies)
- be established in one of the eligible countries, i.e.:
- EU Member States (including overseas countries and territories (OCTs))
- non-EU countries: listed EEA countries and countries associated to the Digital Europe Programme (list of participating countries)
Please note that this call is subject to restrictions due to security reasons. Thus, only the following countries are eligible: EU Member States, EEA countries and Switzerland (participation limited to specific eligible countries). Entities must not be directly or indirectly controlled from a country that is not an eligible country unless the granting authority agrees to allow for exceptional participation on the basis of a guarantee (ownership control restriction).
Proposals must be submitted by
- minimum 7 independent applicants (beneficiaries; not affiliated entities) from 5 different eligible countries
- at least one industrial partner
The consortium can include public and private entities such as (but not limited to): healthcare providing organisations, medtech industry, SMEs, AI/GenAI and IT solution providers, research organisations, governmental authorities (at national, regional, local level), non-governmental organisations representing key stakeholders, such as patients, healthcare professionals, etc.
other eligibility criteria
Specific cases
Natural persons — Natural persons are NOT eligible (with the exception of self-employed persons, i.e. sole traders, where the company does not have legal personality separate from that of the natural person).
International organisations — International organisations are NOT eligible, unless they are International organisations of European Interest within the meaning of Article 2 of the Digital Europe Regulation (i.e. international organisations the majority of whose members are Member States or whose headquarters are in a Member State).
Entities without legal personality — Entities which do not have legal personality under their national law may exceptionally participate, provided that their representatives have the capacity to undertake legal obligations on their behalf, and offer guarantees for the protection of the EU financial interests equivalent to that offered by legal persons.
EU bodies — EU bodies (with the exception of the European Commission Joint Research Centre) can NOT be part of the consortium.
Associations and interest groupings — Entities composed of members may participate as ‘sole beneficiaries’ or ‘beneficiaries without legal personality’.
Countries currently negotiating association agreements — Beneficiaries from countries with ongoing negotiations for participating in the programme (see list of participating countries above) may participate in the call and can sign grants if the negotiations are concluded before grant signature and if the association covers the call (i.e. is retroactive and covers both the part of the programme and the year when the call was launched).
EU restrictive measures — Special rules apply for entities subject to EU restrictive measures under Article 29 of the Treaty on the European Union (TEU) and Article 215 of the Treaty on the Functioning of the EU (TFEU). Such entities are not eligible to participate in any capacity, including as beneficiaries, affiliated entities, associated partners, subcontractors or recipients of financial support to third parties (if any).
EU conditionality measures — Special rules apply for entities subject to measures adopted on the basis of EU Regulation 2020/209221. Such entities are not eligible to participate in any funded role (beneficiaries, affiliated entities, subcontractors, recipients of financial support to third parties, etc). Currently such measures are in place for Hungarian public interest trusts established under the Hungarian Act IX of 2021 or any entity they maintain (see Council Implementing Decision (EU) 2022/2506, as of 16 December 2022).
Additional information
Topics
Relevance for EU Macro-Region
EUSAIR - EU Strategy for the Adriatic and Ionian Region, EUSALP - EU Strategy for the Alpine Space, EUSBSR - EU Strategy for the Baltic Sea Region, EUSDR - EU Strategy for the Danube Region
UN Sustainable Development Goals (UN-SDGs)
project duration
36 months
Additional Information
Proposals must be submitted electronically via the Funding & Tenders Portal Electronic Submission System (accessible via the Topic page in the Calls for proposals section). Paper submissions are NOT possible.
Proposals (including annexes and supporting documents) must be submitted using the forms provided inside the Submission System (NOT the documents available on the Topic page — they are only for information).
Proposals must be complete and contain all the requested information and all required annexes and supporting documents:
- Application Form Part A — contains administrative information about the participants (future coordinator, beneficiaries and affiliated entities) and the summarised budget for the project (to be filled in directly online)
- Application Form Part B — contains the technical description of the project (template to be downloaded from the Portal Submission System, completed, assembled and re-uploaded)
- mandatory annexes and supporting documents (templates to be downloaded from the Portal Submission System, completed, assembled and re-uploaded):
- ownership control declarations (including for associated partners and subcontractors)
Proposals are limited to maximum 70 pages (Part B).
Call documents
Call Document DIGITAL-2026-AI-PILOTING-10Call Document DIGITAL-2026-AI-PILOTING-10(554kB)

