Additionally, INCISIVE’s work will be enriched by an automated Machine Learning (ML)-based annotation mechanism and through the development of an interoperable pan-European federated repository of medical images that will enable the secure donation and sharing of data in compliance with ethical, legal and privacy demands, increasing accessibility to datasets and enabling experimentation of AI-based solutions, towards the large-scale adoption of such solutions in cancer diagnosis, prediction and follow-up.

In its lifetime, INCISIVE will make use of multimodal data sources, including imaging, biological and Electronic Health Record (HER).