Remote patient monitoring using artificial intelligence: Current state, applications, and challenges

This review results show that AI-enabled RPM architectures have transformed healthcare monitoring applications because of their ability to detect early deterioration in patients' health, personalize individual patient health parameter monitoring using federated learning, and learn human behavior patterns using techniques such as reinforcement learning. This review discusses the challenges and trends to adopt AI to RPM systems and implementation issues. The future directions of AI in RPM applications are analyzed based on the challenges and trends.

Remote patient monitoring using artificial intelligence: Current state, applications, and challenges - Shaik - 2023 - WIREs Data Mining and Knowledge Discovery - Wiley Online Library