This project has developed a real-time digital monitoring system that identifies people at risk of sudden cardiac arrest by analyzing their heart signals (ECGs). By combining a machine learning model with cloud-based technology, the system automatically updates each patient’s status and sends alerts if a risk is detected. This enables the partner organization to provide […]
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