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Applying ARtificial Intelligence to Define clinical trajectorieS for personalized predicTiOn and early deTEctiOn of comorbidiTy and muLtimorbidiTy pattErnSARISTOTELES - Applying ARtificial Intelligence to Define clinical trajectorieS for personalized predicTiOn and early deTEctiOn of comorbidiTy and muLtimorbidiTy pattErnS |
Abstract
Atrial fibrillation (AF), a condition that can lead to blood clots and strokes, is at the heart of the ARISTOTELES project. This initiative aims to establish a multinational data platform to develop AI solutions for managing complex diseases with comorbidities. Leveraging innovative AI technology, ARISTOTELES supports patients with AF and other complex conditions by integrating AI into clinical practice. This integration facilitates the creation of personalised risk assessment and management tools, utilizing patient data ethically. The project adopts a holistic approach to AF treatment, focusing on timely diagnosis and intervention to slow disease progression, reduce disability, lower hospitalisation rates, and decrease mortality. Additionally, it seeks to enhance patient adherence to treatment plans.
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Funding entity: European Union – Horizon Europe Start date: 11/2023 End date: 10/2028 Total funding: 5.999.482,50€ Coordinated by: UNIMORE – Università degli Studi di Modena Consortium: Università degli Studi di Modena e Reggio Emilia (Italy), Aalborg Universitet (Denmark), Universidad de Murcia (Spain), Moverim Consulting SRL (Belgium), Iotic Solutions (Spain), Universitetet i Oslo (Norway), Universitatea de Medicina si Farmacie Carol Davila din Bucuresti (Romania), Panepistimio Kritis (Greece), Fondazione per il Tuo Cuore Onlus (Italy), GERS SAS (France) and the University of Coimbra. PI UC: Lino Manuel Martins Gonçalves |
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Project website: https://aristoteles-horizon.eu/
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