AIMC Topic: Diabetes Mellitus, Type 1
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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
Dec 31, 2018
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
Dec 17, 2018
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
Dec 15, 2018
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
Nov 3, 2018
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
Sep 5, 2018
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 ...
Access to Information
Public Health
Big Data
Ethnicity
Decision Support Systems, Clinical
Data Collection
Diabetes Mellitus, Type 2
Racial Groups
Diabetes Mellitus, Type 1
Decision Making
Healthcare Disparities
Genotype
Phenotype
Computational Biology
Precision Medicine
Humans
Language
Artificial Intelligence
Reproducibility of Results
Neural network-based model predictive control for type 1 diabetic rats on artificial pancreas system.
Medical & biological engineering & computing
Aug 1, 2018
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...
Incorporating Unannounced Meals and Exercise in Adaptive Learning of Personalized Models for Multivariable Artificial Pancreas Systems.
Journal of diabetes science and technology
Jul 31, 2018
BACKGROUND: Despite the recent advancements in the modeling of glycemic dynamics for type 1 diabetes mellitus, automatically considering unannounced meals and exercise without manual user inputs remains challenging.
The Promise and Perils of Wearable Physiological Sensors for Diabetes Management.
Journal of diabetes science and technology
Mar 15, 2018
Development of truly useful wearable physiologic monitoring devices for use in diabetes management is still in its infancy. From wearable activity monitors such as fitness trackers and smart watches to contact lenses measuring glucose levels in tears...
Serum 1,5-Anhydroglucitol Concentrations Remain Valid as a Glycemic Control Marker In Diabetes with Earlier Chronic Kidney Disease Stages.
Experimental and clinical endocrinology & diabetes : official journal, German Society of Endocrinology [and] German Diabetes Association
Dec 21, 2017
PURPOSE: To investigate the reliability of 1,5-anhydroglucitol (1,5-AG) in diabetes with mild or moderate renal dysfunction.
Learning ensemble classifiers for diabetic retinopathy assessment.
Artificial intelligence in medicine
Oct 6, 2017
Diabetic retinopathy is one of the most common comorbidities of diabetes. Unfortunately, the recommended annual screening of the eye fundus of diabetic patients is too resource-consuming. Therefore, it is necessary to develop tools that may help doct...
Diabetes Mellitus, Type 1
Risk Assessment
Fuzzy Logic
Time Factors
Decision Trees
Decision Support Systems, Clinical
Electronic Health Records
Machine Learning
Predictive Value of Tests
Diabetes Mellitus, Type 2
Clinical Decision-Making
Decision Support Techniques
Reproducibility of Results
Prognosis
Risk Factors
Humans
Diabetic Retinopathy
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