The ANTIDOTE poject fosters an integrated vision of explainable AI, where low level characteristics of the deep learning process are combined with higher level schemas proper of the human argumentation capacity and will exploit cross-disciplinary competences in deep learning, argumentation and interactivity to support a broader and innovative view of explainable AI.
The eCREAM project will review and retrieve data from the electronic health records used by emergency departments (where large numbers of patients and staff shortages often make ad hoc data collections unattainable) to foster research on quality-of-care in emergency medicine . Bringing together eight countries (France, Greece, Italy, Poland, Slovakia, Slovenia, Switzerland and the UK) and 11 partners, eCREAM will also review and exploit other existing data sources to measure the outcome of the patients. The initiative aims to make data easy to find, interoperable and reusable for clinicians, researchers, policymakers and citizens.
The main objective of the IDEA4RC project is to establish a Data Space for rare cancers (RC) that will make possible the re-use of existing multisource health data (cancer registry data, national registries, data from biobanks etc.) across European healthcare systems leveraging emerging interoperability technologies and AI approaches.