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WILLEM: AI to Reduce Cardiovascular Diseases

Project description

AI for cardiology precision medicine

Heart disease diagnosis involves a combination of heart-monitoring, imaging and blood tests, which are usually interpreted by clinicians. Funded by the European Innovation Council, the WILLEM: AI to Reduce Cardiovascular Diseases project introduces an AI-based platform capable of transforming electrocardiogram (ECG) data into a clinical report. The platform can be used with any ECG monitoring device and can diagnose numerous types of heartbeat irregularities (arrhythmias) as well as atrial fibrillation. Importantly, it can integrate into any clinical workflow and predict progression into cardiovascular disease in an automated manner. Its implementation is expected to minimise physician workload and enhance heart disease detection.

Objective

WILLEM is the first 100% automated cloud platform for electrocardiogram (ECG) analysis, designed to comprehensively identify and diagnose all types of arrhythmias and predict Cardiovascular Diseases (CVDs) behaviour at 6 months since its detection. WILLEM communicates users and
hospitals-in real time through a unique Cloud Platform, integrable with any other eHealth platform as part of the clinical workflow. WILLEM provides the best prospective and labelled ECG database and, as a hardware-agnostic platform, it uses breakthrough Artificial Intelligence (AI) models
to transform raw ECG signals from any monitoring device into a medical grade ECG report. Today, WILLEMs AI classifies 73 arrhythmias of the 288 known cardiac patterns, more than 90% of the cases, and it is the only solution that predicts Atrial Fibrillation. The goal is to classify every
arrythmia present in human biology and to predict the 6 most prevalent heart diseases in an automatic and non-supervised way to reduce CVDs.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-EIC-ACC-BF - HORIZON EIC Accelerator Blended Finance

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Call for proposal

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(opens in new window) HORIZON-EIC-2021-ACCELERATORCHALLENGES-01

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Coordinator

IDOVEN 1903 SL
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 500 000,00
Address
C/PRINCIPE DE VERGARA 128 ESC DR PISO EN
28002 MADRID
Spain

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 3 596 296,00
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