Obtaining Difference Equations for~Glucose Prediction by~Structured Grammatical Evolution and~Sparse Identification

Resumen

Diabetes is one of the most common and difficult non-communicable diseases to deal with in our days. People with diabetes need to keep their glucose levels within a certain range to avoid health complications. Some patients must inject insulin to regulate their glucose levels, and estimating the necessary dose is not an easy task. In this paper, we investigate how to obtain expressions that predict glucose levels using variables such as previous glucose values, food ingestion (in carbohydrates), basal insulin dosing, and dosing of bolus of insulin. This paper proposes the combination of structured grammatical evolution and sparse identification to obtain difference equations governing the dynamics of the glucose levels over time. Glucose prediction serves as a tool for deciding the most convenient insulin dosing. Our technique produces promising results that provide explainable equations and use information usually managed by people with diabetes.

J. Manuel Colmenar

Catedrático de Universidad

Mis intereses de investigación se centran en las metaheurísticas aplicadas a problemas de optimización. He trabajado en diferentes problemas de optimización combinatoria aplicando algoritmos trajectoriales como GRASP o VNS. Además, estoy muy interesado en las aplicaciones de la Evolución Gramatical, específicamente en el dominio de los modelos y la predicción, como alternativa a los enfoques de aprendizaje automático.