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  4. Best Practices: Putting Medical Data at the Heart of Innovation

Best Practices: Putting Medical Data at the Heart of Innovation

No advanced AI solution in healthcare can be developed without relevant data. At the same time, medical data is highly sensitive and must be handled with strict attention to privacy, regulation and trust. AI4Health.Cro recognised this challenge early and made data access one of the key enablers of service delivery.

The project established a focus group with expertise in data acquisition, management, processing and modelling. This group included 10 of the 16 project partners and worked towards building a regulatory sandbox, described in the Project Summary as a secure processing environment. The aim was to allow the extraction of real-life medical data on demand for users, using procedures developed under the European Health Data Space framework by HZJZ, HZZO and the Ministry of Health.

In parallel, the Ruđer Bošković Institute team compiled a catalogue of publicly available datasets that can be used for building AI models, including access rules for different stakeholder groups. This is an important practical step because many SMEs and public sector users do not have prior experience with real-life medical data handling.

AI4Health.Cro also used innovation challenges as a way to demonstrate the secondary use of clinical data in practice. These challenges were designed as open, crowdsourcing activities focused on predefined healthcare digitalisation problems, such as diagnostic, prognostic or clinical decision support tasks. The model was inspired by DREAM Challenges and lasts two to three months.

Two innovation challenges were organised in the two years. The 2024 challenge focused on predicting early patient rehospitalisation within 30 days and attracted 99 applicants, with 27 teams participating. The 2025 challenge focused on detecting suspicious lesions and scoring mammography images, with 106 applicants and 14 participating teams.

For the wider EDIH network, this is a strong example of how data access, regulatory preparation and innovation support can be connected. Rather than treating data as an obstacle, AI4Health.Cro placed it at the centre of innovation, while building safeguards around privacy, anonymisation and secure processing.

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