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, WILLEM’s 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
Programme(s)
Funding Scheme
HORIZON-AG - HORIZON Action Grant Budget-BasedCoordinator
28002 Madrid
Spain
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.