PERFECT-FIT

Cardiovascular disease (CVD) is the leading global cause of mortality and morbidity, with ischemic heart disease (IHD) representing approximately half of all CVD-related deaths. Precise, personalized risk assessment and treatment recommendations are crucial for addressing the diverse population at risk of CVD. Current standard approaches rely on algorithms that incorporate a limited set of traditional risk factors to estimate CVD and IHD risk. However, significant cardiovascular events often occur in individuals categorized as low risk, underscoring the need for ongoing research to enhance preventive strategies. The Focus The MyDigiTwin initiative aims to provide individuals with personalized insights into their cardiac health, enabling proactive monitoring and management of cardiovascular conditions. This integrated digital health platform empowers individuals to take control of their cardiac health by offering accessible, data-driven insights and tools. The Research MyDigiTwin is a pioneering research initiative focused on revolutionizing cardiac health management by integrating advanced AI technologies with extensive patient data. The development of MyDigiTwin involves harnessing large-scale longitudinal datasets from over 500,000 patients, combined with sophisticated AI algorithms. This approach enables the platform to analyze diverse health parameters and generate tailored recommendations for users based on their unique health profiles. By leveraging AI and comprehensive patient data, MyDigiTwin represents an innovative approach to preventive and personalized healthcare, facilitating early detection and intervention for cardiovascular conditions. Origin This project was funded within the Big Data & Health Program. The focus of this public-private research program is the use of big data for the early detection and prevention of cardiovascular diseases. The program has been developed by NWO, ZonMw, the Dutch Heart Foundation, the Top Sectors Life Sciences & Health (LSH), ICT and Creative Industry, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center. Within this research program, the ambitions of the Dutch Heart Foundation, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center were aligned with the ambitions of Commit2Data for the Top Sectors ICT, LSH, and Creative Industry, as described in the 2018-2019 Kennis- en Innovatiecontracts between NWO and the Top Sectors.

The correct interpretation of electrocardiograms (ECGs) is crucial for accurately diagnosing cardiac abnormalities. Current methods, both manual by physicians and computerized, have not achieved the level of accuracy comparable to cardiologists in detecting acute cardiac issues. Leveraging advancements in artificial intelligence and big data, particularly deep neural networks, offers promising avenues to improve ECG interpretation where traditional methods have fallen short. The ECG-Project develops deep learning algorithms to automate ECG interpretation, particularly focusing on areas where current methods are inadequate. Through this research, we aim to revolutionize ECG interpretation, improving diagnostic accuracy, reducing healthcare resource utilization, and ultimately enhancing patient outcomes. The Research The project objectives are: WP1: Creating an algorithm capable of accurately and swiftly triaging ECGs through transfer learning, uncovering features in diseases with unknown ECG characteristics (such as primary arrhythmia syndromes and genetic disorders). WP2: design a portable multi-lead ecg-device, suitable for use by patients at home and healthcare professionals. This device will enable high-quality ECG acquisitions for rapid diagnosis. Origin This project is funded within the Innovative Medical Devices Initiative (IMDI) program 'Heart for Sustainable Care'. The focus of this program is the development of medical technology for the earlier detection, monitoring, and better treatment of cardiovascular diseases to ensure accessible healthcare and sufficient staffing. The program has been developed and funded by the Dutch Heart Foundation, ZonMw and NWO, who collaborate within the Dutch CardioVascular Alliance.