AI in Remote Patient Monitoring

TL;DR

This paper reviews how AI enhances remote patient monitoring by improving accuracy, predictive analytics, and personalized care, discussing current applications, challenges, and future prospects in healthcare technology.

Contribution

It provides a comprehensive overview of AI integration in RPM, including system architectures, real-world applications, and future challenges, highlighting recent advancements and case studies.

Findings

AI improves monitoring accuracy and predictive analytics.

AI enables personalized treatment plans in RPM.

The paper discusses challenges and future directions in AI-driven RPM.

Abstract

The rapid evolution of Artificial Intelligence (AI) has significantly transformed healthcare, particularly in the domain of Remote Patient Monitoring (RPM). This chapter explores the integration of AI in RPM, highlighting real-life applications, system architectures, and the benefits it brings to patient care and healthcare systems. Through a comprehensive analysis of current technologies, methodologies, and case studies, I present a detailed overview of how AI enhances monitoring accuracy, predictive analytics, and personalized treatment plans. The chapter also discusses the challenges and future directions in this field, providing a comprehensive view of AI's role in revolutionizing remote patient care.