SOURCE-LINKED INTELLIGENCE

Applying ARtificial Intelligence to Define clinical trajectorieS for personalized predicTiOn and early deTEctiOn of comorbidiTy and muLtimorbidiTy pattErnS

CORDIS · observation · Publication date unknown

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 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

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

4093462.5

unit

EUR