AI-Enabled Remote Patient Monitoring for Early Detection of Cardiovascular Events

Abstract

This paper introduces an AI-enabled remote patient monitoring system designed to detect early signs of cardiovascular events. Leveraging machine learning algorithms, our system analyzes continuous streams of physiological data collected from wearable sensors to identify patterns indicative of impending cardiovascular events, such as arrhythmias or ischemic events. By providing real-time alerts to healthcare providers, this system enables timely interventions, reduces the risk of adverse outcomes, and enhances patient safety in remote monitoring settings.