Nonlinear Model Predictive Control and System Identification for a Dual-hormone Artificial Pancreas [PDF]
arXiv, 2022 In this work, we present a switching nonlinear model predictive control (NMPC) algorithm for a dual-hormone artificial pancreas (AP), and we use maximum likelihood estimation (MLE) to identify model parameters. A dual-hormone AP consists of a continuous glucose monitor (CGM), a control algorithm, an insulin pump, and a glucagon pump. The AP is designed
arxiv
Journal of Nepal Medical Association, 2021 Introduction: Drug-drug interaction is one of the causes of adverse drug reactions. Generally, drug-drug interaction is common in multidrug therapy.
Lujaw Ratna Tuladhar +4 more
doaj +1 more source
Patterns Detection in Glucose Time Series by Domain Transformations and Deep Learning [PDF]
arXiv, 2023 People with diabetes have to manage their blood glucose level to keep it within an appropriate range. Predicting whether future glucose values will be outside the healthy threshold is of vital importance in order to take corrective actions to avoid potential health damage.
arxiv
Investigating Speed Deviation Patterns During Glucose Episodes: A Quantile Regression Approach [PDF]
arXiv, 2023 Given the growing prevalence of diabetes, there has been significant interest in determining how diabetes affects instrumental daily functions, like driving. Complication of glucose control in diabetes includes hypoglycemic and hyperglycemic episodes, which may impair cognitive and psychomotor functions needed for safe driving.
arxiv
Safety and efficacy of gliclazide as treatment for type 2 diabetes: a systematic review and meta-analysis of randomized trials. [PDF]
PLoS ONE, 2014 OBJECTIVE AND DESIGN: Gliclazide has been associated with a low risk of hypoglycemic episodes and beneficial long-term cardiovascular safety in observational cohorts.
Gijs W D Landman +8 more
doaj +1 more source
A function approximation approach to the prediction of blood glucose levels [PDF]
arXiv, 2021 The problem of real time prediction of blood glucose (BG) levels based on the readings from a continuous glucose monitoring (CGM) device is a problem of great importance in diabetes care, and therefore, has attracted a lot of research in recent years, especially based on machine learning.
arxiv
A parsimonious model of blood glucose homeostasis [PDF]
arXiv, 2021 The mathematical modelling of biological systems has historically followed one of two approaches: comprehensive and minimal. In comprehensive models, the involved biological pathways are modelled independently, then brought together as an ensemble of equations that represents the system being studied, most often in the form of a large system of coupled
arxiv
EFFECT OF CHLOROQUINE ON BLOOD GLUCOSE LEVELS IN PATIENTS WITH NON INSULIN DEPENDENT DIABETES MELLITUS [PDF]
Acta Medica Iranica, 1998 77irty six patients with non insulin dependent diabetes mellitus, whose blood sugar was not controlled with maximal doses of oral hypoglycemic agents and did not accept insulin treatment, were selected for this study.
H. Mostafavi
doaj +2 more sources
Vildagliptin and its role in the treatment of diabetes mellitus
Сахарный диабет, 2010 Type 2 diabetes mellitus is a most serious medical problem throughout the world. Traditional hypoglycemic agents do not ensure long-term control ofglycemia and fail to affect the natural course of DM.
Yury Shavkatovich Khalimov
doaj +1 more source
Intermittent Control for Safe Long-Acting Insulin Intensification for Type 2 Diabetes: In-Silico Experiment [PDF]
arXiv, 2023 Around a third of type 2 diabetes patients (T2D) are escalated to basal insulin injections. Basal insulin dose is titrated to achieve a tight glycemic target without undue hypoglycemic risk. In the standard of care (SoC), titration is based on intermittent fasting blood glucose (FBG) measurements.
arxiv