Abstract
Cancer research is increasing relying on data-driven methods and Artificial Intelligence (AI), to increase accuracy and efficiency in decision making. Such methods can solve a variety of clinically relevant problems in cancer diagnosis and treatment, provided that an adequate data availability is ensured. The generation of multicentric data repositories poses a series of integration and harmonization challenges. This work discusses the strategy, solutions and further issues identified along this procedure within the EU project INCISIVE that aims to generate an interoperable pan-European federated repository of medical images and an AI-based toolbox for medical imaging in cancer diagnosis and treatment.Clinical Relevance- Supporting the integration of medical imaging data and related clinical data into large interoperable repositories will enable the development, and validation, and wider adoption of AI-based methods in cancer diagnosis, prediction, treatment and follow-up.
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