WEAR
The WEAR clinical trial focuses on leveraging AI for ECG analysis to reduce the time spent by clinical staff analyzing Holter recordings. It also targets at improving the early detection of atrial fibrillation (AF), a leading cause of strokes and global disability. The study plans to enroll 1,500 patients and employ ECG devices like Holters and wearable extended-wear patches integrated with Philips Cardiologs’ AI platform. This cloud-based solution detects ECG abnormalities using AI, reducing manual review, and streamlining workflows for faster diagnoses. Key objectives include: - Developing and validating AI algorithms for arrhythmia detection and reporting, ensuring safe adoption in European healthcare settings. - Implementing AI and cloud technology in care pathways to optimize patient referrals and overall healthcare efficiency. - Using the platform for cryptogenic stroke patients to enable faster AF detection and timely initiation of NOAC treatment. By addressing bottlenecks like the scarcity of cardiology staff, the study seeks to expand healthcare system capacity and time to diagnosis through broader adoption of AI-driven diagnostics.
This pathway is currently under development. More information will be available soon.