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Combining data augmentation, EDAs and grammatical evolution for blood glucose forecasting., , , , and . Memetic Comput., 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)Data augmentation and evolutionary algorithms to improve the prediction of blood glucose levels in scarcity of training data., , , , , , and . CEC, page 2193-2200. IEEE, (2017)Predicting Glycemia in Diabetic Patients By Evolutionary Computation and Continuous Glucose Monitoring., , , , , and . GECCO (Companion), page 1393-1400. ACM, (2016)Data-Based Identification of Prediction Models for Glucose., , , , , , , , and . GECCO (Companion), page 1327-1334. ACM, (2015)Swarm hybrid optimization for a piecewise model fitting applied to a glucose model., , , , , and . J. Systems and IT, 20 (4): 404-416 (2018)Evolving Classification Rules for Predicting Hypoglycemia Events., , , , and . CEC, page 1-8. IEEE, (2022)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)Experimental Characterization of a MMW Signal Generation Approach Based on Optical Phase Modulation and Optical Filtering for Data Transmission over a Directly Modulated Laser., , and . ICTON, page 1-4. IEEE, (2023)