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Article Abstract
The integration of telehealth, particularly remote monitoring (RM), has profoundly improved the care of patients with cardiac implantable electronic devices (CIEDs). The recent COVID-19 pandemic has further accelerated the adoption of RM systems. The implementation of RM to standard clinical care has been accompanied by a surge of device transmissions. Especially unscheduled transmissions have resulted in an overwhelming workload for clinicians. As the number of device transmissions is expected to increase further while clinical resources remain limited, workflow optimization is crucial. Artificial intelligence (AI) presents a promising solution. This review outlines recent advances in RM and AI applications for CIEDs. It explores the potential of AI to streamline RM workflows, reduce clinician workload, and enhance heart failure care by enabling early detection of clinical deterioration and timely intervention. In addition, key barriers to implementation are addressed, including data standardization and regulatory considerations. Beyond improving monitoring efficiency and patient outcomes, AI-supported RM may also help expand access to care through more effective resource allocation and contribute to a more sustainable, future-proof healthcare system.
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