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Applying ARtificial Intelligence to Define clinical trajectorieS for personalize...

Applying ARtificial Intelligence to Define clinical trajectorieS for personalized predicTiOn and early deTEctiOn of comorbidiTy and muLtimorbidiTy pattErnS The ARISTOTELES project aims to build a multinational harmonized data platform to develop and implement novel artificial intelligence (AI) approaches for management of complex diseases, where progression and manifestations of como... see more

31/10/2028

UNIMORE

4M€

Project Budget: 4M€

Project leader

UNIVERSITA DEGLI STUDI DI MODENA E REGGIO EMI... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

Financing granted El organismo HORIZON EUROPE notifico la concesión del proyecto The day 2023-11-01

HORIZON-HLTH-2022-STAYHLTH-01-05-two-stage: Prevention of obesity throughout th... Expected Outcome:This topic aims at supporting activities that are enabling or contributing to one o...

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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UNIMORE

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Project duration: 59 months Date Start: 2023-11-01
End date: 2028-10-31

Project leader

UNIVERSITA DEGLI STUDI DI MODENA E REGGIO EMI... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 4M€

participation deadline Sin fecha límite de participación.

Project description The ARISTOTELES project aims to build a multinational harmonized data platform to develop and implement novel artificial intelligence (AI) approaches for management of complex diseases, where progression and manifestations of comorbidities are via multiple interacting pathways. We aim to apply our novel approach to a population of great need due to atrial fibrillation (AF), but our outputs can be extended to other complex diseases with multimorbidity. By integrating AIs into clinical practice, our platform will form a backbone for acceptable, responsible, and respectful uses of patient/participant data to develop and validate novel trustworthy AI tools for more personalized risk assessment and management. This represents a paradigm shift in AF treatment, moving from a focus on individual risk factors and selected outcomes (eg. stroke) to a holistic approach, underpinning timely diagnostic and therapeutic interventions to reduce disease progression, disability, hospitalizations and mortality, as well as improve patient adherence to lifestyle modifications, medications, and other treatment regimens.ARISTOTELES will be delivered through 8 inter-linking work-packages (WPs): WP1 is study management/coordination. WP2 provides the ethical/legal requirements for the development of a trustworthy AI. WP3 addresses stakeholder understanding of AI, needs assessment, and engagement in all the phases of the AI development. In WP4, granular data on genotype and phenotype characteristics, are harmonized from different datasets into a common platform. In WP5, AI algorithms/tools are developed and connected to an interactive output interface for patients and clinicians. In WP6, we test the AI tool developed in WP5 in a clinical trial simulation (in silico trial). In WP7 a multicenter randomized trial runs across multiple countries including both primary care and secondary care. WP7 and WP8 drive the clinical implementation and dissemination of results.

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