WARIFA "Watching the risk factors: Artificial intelligence and the prevention of chronic conditions" (DIT.AD021.131)
Project areaMatematica Applicata (DIT.AD021)
Structure responsible for the research project
Digital healthcare may prevent poor health. Personalised early risk prediction by artificial intelligence can empower citizens to adopt healthier habits and a better lifestyle. This project aims at defining a general personalised early risk prediction model that will be used to support individual preventive measures as well as early intervention. New digital tools are designed to empower both citizens and patients. Furthermore, the impact of the new digital tools on health and care pathways are investigated. Three main scenarios are included: 1. Chronic sun damage and the fight against skin cancer, 2. The late complications of diabetes mellitus and 3. The four main lifestyle risk factors in noncommunicable diseases. All data in the project are analysed in a multidisciplinary approach including medical, sociological and behavioural outcomes.
The main objectives of the WARIFA project are to: 1. Develop a technical prototype of a comprehensive AI-based system to provide person-centred integrated early risk prediction for multiple CCs. The main components of the system will be in place on a central server which individual citizens and patients can access on their smartphone via the WARIFA app. The integrated risk prediction enables the system to provide and improve access to preventive care within the healthcare system. The WARIFA AI-based prototype will collect ubiquitous data (i.e., both user-generated data and available public data) that will be used to assess the integrated risk of multiple CCs. The combined risk assessment enables the creation of a personalized set of recommendations on lifestyle and health education; 2. Gain knowledge on how the WARIFA prototype may be used for early risk assessment and monitoring, and prevention interventions in individual citizens, especially in vulnerable, high- risk, or "hard to reach" population subgroups; 3 Provide a model framework for future health intervention strategies based on AI and big data technologies.
Start date of activity
Digital healthcare, prediction model, artificial intelligence based sistem
Last update: 09/12/2023