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TIMELY- A patient-centered early risk prediction, prevention, and intervention platform to support the continuum of care in coronary artery disease (CAD) using eHealth and artificial intelligence.

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Background

Coronary artery disease (CAD) remains the leading cause of disease burden globally. CAD develops slowly, usually over decades, and depends on multiple (often modifiable) risk factors and their interactions. Self-management and patient activation are of rising importance as current restrictions in healthcare budgets impose great difficulties to enable the provision of qualitative secondary prevention to all cardiac patients in an era facing a huge cardiovascular disease epidemic.

Main hypothesis of TIMELY

The main hypothesis in the patient-centered TIMELY pathway, is that a modular, collaborative eHealth platform, supported by Artificial Intelligence (AI) for the continuous and in-time prediction of cardiac risks and complications and the induction of targeted behavioural change interventions, can be effective and cost-efficient for the secondary prevention of CAD by limiting the physiological and psychological effects of the disease and improving risk factor and symptom management. Improvements in patients’ self-care and empowerment and clinicians’ efficiency are also expected.

TIMELY Platform

Along the continuum of the disease, prediction of the individual risk for disease progression, including physical impairment and severe events, is mandatory for timely intervention. TIMELY is a platform that provides AI-powered apps and dashboards and decision support tools assisting patients and clinicians to personalize healthcare based on risk evaluation, outcome prediction and tailored interventions. The platform will be developed based on a functional platform for Interoperability with electronic health records and security mechanisms, to ensure information completeness and continuity and to simplify data sharing. AI in TIMELY, built with big retrospective datasets of >23.000 CAD patients, will constantly monitor and evaluate risks and will indicate any deviation from defined therapy goals or unfavorable changes as well as propose proper interventions.

Capemed Role

  • Analysis of retrospective and prospective datasets in order to build risk prediction models addressing MACCE, low adherence to and ineffeciency of the interventions.

  • Design and implementation of Artificial intelligence for prescription of personalised exercise plans and optimal results.

  • Design and deployment of Decision Support Tools for cardiac rehabilitation.

Funding

TIMELY is being funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No [101017424]. 

 

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