Artificial intelligence biosensors for continuous glucose monitoring
Xiaofeng Jin, Andrew Cai, Tailin Xu, Xueji Zhang
Abstract
Abstract Artificial intelligence (AI) algorithms in combination with continuous monitoring technologies have the potential to revolutionize chronic disease management. The recent innovations in both continuous glucose monitoring (CGM) and the closed‐loop highlight the far‐reaching potential of AI biosensors for individual healthcare. This review summarizes some of the most advanced progress made in CGM biosensing. We will focus on three main applications of AI algorithms in diabetes management: closed‐loop control algorithms, glucose predictions, and calibrations. The challenges and opportunities of AI technologies for CGM in individualized and proactive medicine will also be discussed.
Topics & Concepts
Continuous glucose monitoringClosed loopComputer scienceApplications of artificial intelligenceBiosensorContinuous monitoringDiabetes managementRisk analysis (engineering)Artificial intelligenceNanotechnologyEngineeringDiabetes mellitusMedicineType 1 diabetesOperations managementControl engineeringMaterials scienceType 2 diabetesEndocrinologyElectrochemical sensors and biosensorsBiosensors and Analytical DetectionPancreatic function and diabetes