Advancements in Glucose Control Systems Based on Mathematical Models and Data-Driven Computations

Abstract

This survey reviews glucose regulatory systems using mathematical methods. We discuss the utilization of various minimal and comprehensive models of glucose metabolism combined with model predictive control, data assimilation, and physics-informed neural networks to develop decision support systems. These systems will help doctors and nurses administrating insulin levels in patients with diabetes and those in intensive care units.