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Data-Based Identification of Prediction Models for Glucose., , , , , , , , and . GECCO (Companion), page 1327-1334. ACM, (2015)Predicting Glycemia in Diabetic Patients By Evolutionary Computation and Continuous Glucose Monitoring., , , , , and . GECCO (Companion), page 1393-1400. ACM, (2016)A genetic algorithm approach to customizing a glucose model based on usual therapeutic parameters., , , and . Progress in AI, 6 (3): 255-261 (2017)Swarm hybrid optimization for a piecewise model fitting applied to a glucose model., , , , , and . J. Systems and IT, 20 (4): 404-416 (2018)Enhancing Grammatical Evolution Through Data Augmentation: Application to Blood Glucose Forecasting., , , , , , , and . EvoApplications (1), volume 10199 of Lecture Notes in Computer Science, page 142-157. (2017)Forecasting glucose levels in patients with diabetes mellitus using semantic grammatical evolution and symbolic aggregate approximation., , , , , and . GECCO (Companion), page 1387-1394. ACM, (2017)Modeling glycemia in humans by means of Grammatical Evolution., , , , , , and . Appl. Soft Comput., (2014)Combining data augmentation, EDAs and grammatical evolution for blood glucose forecasting., , , , and . Memetic Computing, 10 (3): 267-277 (2018)Clarke and parkes error grid analysis of diabetic glucose models obtained with evolutionary computation., , , , , , , , and . GECCO (Companion), page 1305-1312. ACM, (2014)