AI in Continuous Blood Glucose Monitoring Systems
Authors:-Nagesh M S
Abstract-Continuous Blood Glucose Monitoring (CGM) systems have revolutionized diabetes management by providing real-time insights into glucose fluctuations, enabling patients and healthcare providers to take proactive measures. The integration of Artificial Intelligence (AI) into CGM systems has significantly enhanced their efficiency, accuracy, and predictive capabilities. AI algorithms analyze complex and voluminous glucose data to identify patterns, predict future trends, and offer personalized recommendations. This paper explores the applications of AI in CGM, examining how machine learning and deep learning models are being used for improved glycemic control, early detection of glucose anomalies, behavior prediction, and adaptive insulin therapy. It also discusses the impact of AI-driven CGMs on patient engagement, remote monitoring, and clinical decision-making. Ethical concerns, data privacy, and technological limitations are also addressed. This comprehensive analysis underscores AI’s transformative role in reshaping diabetes care, making it more precise, predictive, and patient-centric.
