Bolus calculators

S Schmidt, K Nørgaard - Journal of diabetes science and …, 2014 - journals.sagepub.com
Matching meal insulin to carbohydrate intake, blood glucose, and activity level is
recommended in type 1 diabetes management. Calculating an appropriate insulin bolus …

Guidelines for optimal bolus calculator settings in adults

J Walsh, R Roberts, T Bailey - Journal of diabetes science …, 2011 - journals.sagepub.com
Bolus insulin calculators (BCs) became available in insulin pumps in 2002 and are being
integrated into glucose meters and portable device applets for use with multiple daily …

Multivariable adaptive identification and control for artificial pancreas systems

K Turksoy, L Quinn, E Littlejohn… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
A constrained weighted recursive least squares method is proposed to provide recursive
models with guaranteed stability and better performance than models based on regular …

A statistical virtual patient population for the glucoregulatory system in type 1 diabetes with integrated exercise model

N Resalat, J El Youssef, N Tyler, J Castle, PG Jacobs - PloS one, 2019 - journals.plos.org
Purpose We introduce two validated single (SH) and dual hormone (DH) mathematical
models that represent an in-silico virtual patient population (VPP) for type 1 diabetes (T1D) …

Assessing the risk of ketoacidosis due to sodium-glucose cotransporter (SGLT)-2 inhibitors in patients with type 1 diabetes: a meta-analysis and meta-regression

G Musso, A Sircana, F Saba, M Cassader… - PLoS …, 2020 - journals.plos.org
Background Sodium-glucose cotransporter-2 (SGLT2) inhibitors (SGLT2i) showed benefits
in type 1 diabetes mellitus (T1DM), but the risk of diabetic ketoacidosis (DKA) limits their use …

A practical approach to using trend arrows on the Dexcom G5 CGM system to manage children and adolescents with diabetes

LM Laffel, G Aleppo, BA Buckingham… - Journal of the …, 2017 - academic.oup.com
Practical Approach to Using Trend Arrows on the Dexcom G5 CGM System to Manage
Children and Adolescents With Diabetes | Journal of the Endocrine Society | Oxford Academic …

Model-free machine learning in biomedicine: Feasibility study in type 1 diabetes

E Daskalaki, P Diem, SG Mougiakakou - PloS one, 2016 - journals.plos.org
Although reinforcement learning (RL) is suitable for highly uncertain systems, the
applicability of this class of algorithms to medical treatment may be limited by the patient …

Towards personalization of diabetes therapy using computerized decision support and machine learning: some open problems and challenges

K Donsa, S Spat, P Beck, TR Pieber… - Smart Health: Open …, 2015 - Springer
Diabetes mellitus (DM) is a growing global disease which highly affects the individual
patient and represents a global health burden with financial impact on national health care …

Therapy settings associated with optimal outcomes for t: slim X2 with control-IQ technology in real-world clinical care

LH Messer, MD Breton - Diabetes Technology & Therapeutics, 2023 - liebertpub.com
Objective: To determine insulin dosing parameters that are associated with and predict
optimal outcomes for people using t: slim X2 with Control-IQ technology (CIQ). Methods …

Artificial pancreas system with unannounced meals based on a disturbance observer and feedforward compensation

R Sanz, P García, JL Díez… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This brief is focused on the closed-loop control of postprandial glucose levels of patients
with type 1 diabetes mellitus after unannounced meals, which is still a major challenge …