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Intermittent Control for Safe Long-Acting Insulin Intensification for Type 2 Diabetes: In-Silico Experiments *.

, , , , and . CCTA, page 534-539. IEEE, (2023)

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Model predictive control with sub-frequency actuation for long acting insulin treatment in type 2 diabetes., , , , and . CCTA, page 914-919. IEEE, (2019)Early Glycemic Control Assessment Based on Consensus CGM Metrics*., , , , , and . EMBC, page 1269-1275. IEEE, (2021)Estimating a Personalized Basal Insulin Dose from Short-Term Closed-Loop Data in Type 2 Diabetes., , , , and . CDC, page 2580-2585. IEEE, (2022)A deep learning approach to adherence detection for type 2 diabetics., , , , , and . EMBC, page 2896-2899. IEEE, (2017)Modelling the glucose-insulin system of type 2 diabetes patients using ARMAX models., , , , and . ANZCC, page 88-93. IEEE, (2019)Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional normalization method., and . BMC Bioinform., (2006)Optimal Experimental Design to Estimate Insulin Response in Type 2 Diabetes., , , , and . CCTA, page 540-545. IEEE, (2023)Fast Assessment of Glycemic Control based on Continuous Glucose Monitoring Data., , , , , , and . EMBC, page 7185-7188. IEEE, (2019)Modelling of fasting glucose-insulin dynamics from sparse data*., , , and . EMBC, page 2354-2357. IEEE, (2018)Intermittent Control for Safe Long-Acting Insulin Intensification for Type 2 Diabetes: In-Silico Experiments *., , , , and . CCTA, page 534-539. IEEE, (2023)