Published Paper Details:

This study focuses on the application of AI in remote patient monitoring for improvement of chronic disease management. Chronic diseases continuously pose serious problems for healthcare systems across the globe that can only be resolved by maintaining systematic monitoring and management to avoid complications and improve patient outcomes [1]. Remote patient monitoring (RPM) has become one of the main technologies for delivering proactive preventive care to patients with chronic conditions, providing real-time monitoring of vital signs and symptoms directly from the patients' home environment. AI technologies employed by RPM systems can be used to administer advanced analytics and predictive modeling and help in early detection of signs of deterioration, personalized interventions and adjusting treatment plans [1]. This report analyzes the research problem, conducts thorough literature search, and evaluates the effect of AI-enabled RPM for the management of chronic diseases in the United States, as well as its future implications for healthcare delivery transformation.AI enabled RPMs are capable of finding the best solution to the problems and cut the healthcare expenses drastically by preventing needless clinic visits, hospitalizations, or even emergency room visits. This enables healthcare providers to remotely monitor patients' health status and intervene early when warning signs of deterioration appear. The healthcare system can hence prevent costly complications and decrease the overall health burden. AI algorithms can make it possible to study whole population data and thereby find the most high-risk patient cohorts, who could be then intervened in and involved in activities dedicated to them, the result of which will be better resource allocation and better outcomes for both the patients and all the population