Research Project
SmartCHANGE: Artificial Intelligence for healthier children and youth
SmartCHANGE uses machine-learning methods, that can train models on heterogeneous datasets (i.e. behaviour, fitness levels, biomarkers), to enable accurate risk prediction for people of various ages; while federated learning techniques are employed to ensure data privacy. These methods are leveraged to design two apps: one for health professionals and the other for citizens, which are able to communicate in a bi-directional manner and reduce long-term risk of NCDs. Engineering is responsible for the development of a web-app for health professionals, which integrates an explainable Clinical Decision Support System and for the overall architecture design and subsequent configuration, based on microservices paradigm.
The project has received co-funding from the European Union's Horizon Europe programme - Contract No. 101080965.
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. The European Union cannot be held responsible for them.
Reduce long-term risk of NCDs
Increase data availability for research
Improve health literacy among children and youth
Maximise long term savings for health systems
Impacts
From Data to Artificial Intelligence: Services, Products, and Processes for Future-Proof Business.
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QLMD: Quantum Computing for an efficient urban logistical ecosystem
Applying Quantum Computing to urban logistics to optimize routes, reduce costs and emissions, improve sustainability, and tackle complex problems with scalable solutions.
Implementation and deployment of the Regional Electronic Health Record for Healthcare Entities in Abruzzo
Elevating the digitalization of care and assistance processes in hospitals.
Reengineering of the Health Record of the Regione Molise
The evolution will facilitate information sharing among healthcare facilities and ensure citizens access to an integrated and coordinated service.
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