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Diabetes Mellitus, Type 1

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Convolutional Recurrent Neural Networks for Glucose Prediction.

IEEE journal of biomedical and health informatics
Control of blood glucose is essential for diabetes management. Current digital therapeutic approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and insulin bolus calculators leverage machine learning techniques for pr...

Risk-based postprandial hypoglycemia forecasting using supervised learning.

International journal of medical informatics
BACKGROUND: Predicting insulin-induced postprandial hypoglycemic events is critical for the safety of type 1 diabetes patients because an early warning of hypoglycemia facilitates correction of the insulin bolus before its administration. The postpra...

Prediction of Hypoglycemia During Aerobic Exercise in Adults With Type 1 Diabetes.

Journal of diabetes science and technology
BACKGROUND: Fear of exercise related hypoglycemia is a major reason why people with type 1 diabetes (T1D) do not exercise. There is no validated prediction algorithm that can predict hypoglycemia at the start of aerobic exercise.

Quantitation of serum 25(OH)D2 and 25(OH)D3 concentrations by liquid chromatography tandem mass spectrometry in patients with diabetes mellitus.

Journal of food and drug analysis
Vitamin D has been considered to regulate calcium and phosphorus homeostasis and to preserve skeletal integrity. Serum 25-hydroxyvitamin D (25(OH)D) is the best indicator of vitamin D levels. The association of serum 25(OH)D deficiency with increased...

A Dual Mode Adaptive Basal-Bolus Advisor Based on Reinforcement Learning.

IEEE journal of biomedical and health informatics
Self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) are commonly used by type 1 diabetes (T1D) patients to measure glucose concentrations. The proposed adaptive basal-bolus algorithm (ABBA) supports inputs from either SMBG...

Non-invasive prediction of blood glucose trends during hypoglycemia.

Analytica chimica acta
Over the last four decades, there has been a pursuit for a non-invasive solution for glucose measurement, but there is not yet any viable product released. Of the many sensor modalities tried, the combination of electrical and optical measurement is ...

Serum adipocytokines are associated with microalbuminuria in patients with type 1 diabetes and incipient chronic complications.

Diabetes & metabolic syndrome
AIMS: Recent studies have implicated possible contribution of adipocytokines in development and progression of microvascular complications in patients with type 1 diabetes (T1DM). The aim of our study was to investigate relationship between adipocyto...

Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.

Journal of diabetes science and technology
In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care. With the creation of new sensors for physiological monitoring sensors and the introduction of smart insulin pens, novel data relationships based on ...

Neural network-based model predictive control for type 1 diabetic rats on artificial pancreas system.

Medical & biological engineering & computing
Artificial pancreas system (APS) is a viable option to treat diabetic patients. Researchers, however, have not conclusively determined the best control method for APS. Due to intra-/inter-variability of insulin absorption and action, an individualize...