PERFECT-FIT

2020

Smoking tobacco and physical inactivity are key preventable risk factors of cardiovascular disease (CVD). Perfect Fit aims to prevent CVD, promote well-being, and reduce healthcare costs, particularly targeting disadvantaged populations where smoking and physical inactivity are prevalent.

The Research
The project develops tailored, evidence-based, near real-time computer coaching for quitting smoking and enhancing PA. For every individual, a personal model is designed which generates personalized recommendations based on high-quality existing and newly collected data, and adapts to changing circumstances/progress (similar to a TomTom navigation system), using machine learning techniques and incorporating domain-specific expert knowledge (e.g. health behaviour change strategies). Virtual coaches (VCs) communicate advice in a motivating way that fits individuals’ persuasive communication styles.

Perfect Fit integrates big-data science, sensor technology, and personalized real-time feedback to support smoking cessation and promote adequate physical activity (in both gym settings and daily life). The key questions of this study are:

  • Which adaptivity is needed to create a robust, safe, and effective interaction between individuals and machines?
  • How can we develop advanced data science methods and embed this in current smoking cessation and PA coaching practice?
  • How do measurement modalities, feedback and communication affect individuals’ smoking status and PA?

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.

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CUSTOM-AF

2020
Individuals with atrial fibrillation are at increased risk of an ischemic stroke. Active detection of atrial fibrillation (AF) and optimal referral and treatment of patients could prevent an estimated 1500 ischemic strokes annually. Effective collaboration between primary and secondary care professionals is essential for achieving this goal of stroke prevention attributed to AF. This is the primary objective of the implementation consortium known as CUSTOM-AF. The origin  The CUSTOM-AF was founded in June 2020 and restarted in 2022. CUSTOM-AF implementation consortium aims to share successful practice examples with regional networks and develop guidelines for organizing active detection and integrated care within a network. Additionally, consortium partners seek innovative methods for general practitioners to detect and manage AF without necessitating hospital referrals. With this consortium, the Dutch Heart Foundation, NVVC Connect, Harteraad, and the Dutch CardioVascular Alliance, all work together towards optimal care for patients with AF. The Dutch College of General Practitioners (NHG) serves as a key advisor to the consortium. Earlier detection and better treatment of atrial fibrillation, the most common cardiac arrhythmia in adults, is an important part of the cardiovascular disease research agenda that the Dutch Heart Foundatoin set in 2014, which funds the CUSTOM-AF consortium. The Research The scope of the consortium has been expanded to include two disorders: heart failure and AF. The consortium has undertaken significant initiatives over the past two years (2020-2022) to advance its objectives: Guideline Development: The consortium developed the "Screening and Treatment Optimization for AF" guideline, designed to facilitate early detection of AF within regional healthcare systems. Cost-Effectiveness Analysis: A comprehensive analysis conducted to assess various screening scenarios for AF, evaluating the economic feasibility of different approaches. Thematic Collaboration: In early 2022, a thematic collaboration titled "Juiste Hartzorg op de Juiste Plek" was established in partnership with the Heart Foundation and ZonMw. This collaboration secured funding for 22 regions to support transmural collaboration on AF and HF, with a focus on early detection and treatment optimization. Moving forward from September 2022, NVVC Connect will intensify support for the regions by emphasizing continuous improvement through the PDCA cycle, facilitating knowledge sharing, and implementing innovative approaches. These efforts are aimed at strengthening collaboration and improving outcomes in AF and HF care across the participating regions.
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ECG project UMCU

2020
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.
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