Integrating AI Technologies into Remote Monitoring Patient Systems

Abstract

Improving RPM through AI includes various aspects of healthcare delivery that make systems more efficient, accurate and patient-centric. In this work, the impact and role of AI is explored with a focus on RPM. As a result of the research, it was found that the AI-supported architectures in building RPM have transformed, augmented, and revealed new possibilities of applications and benefits in remote health monitoring. Nine groups of significant AI applications leading to the transformation of remote patient care are identified, analyzed, and discussed. Challenges facing RPM are also discussed. Addressing these challenges requires collaboration among healthcare providers, technology developers, policymakers, and patients to ensure the successful implementation and widespread adoption of remote patient monitoring. The results of this research will allow for an informed decision about the need, benefits, and effectiveness of building a specific AI-based RPM and developing such an architecture with the necessary applications for the specific medical organization.

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