AIMC Topic: Blood Glucose
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Blood glucose concentration prediction based on VMD-KELM-AdaBoost.
Medical & biological engineering & computing
Sep 12, 2021
The time series of blood glucose concentration in diabetic patients are time-varying, nonlinear, and non-stationary. In order to improve the accuracy of blood glucose prediction, a multi-scale combination short-term blood glucose prediction model was...
Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes.
Canadian journal of diabetes
Sep 6, 2021
OBJECTIVES: Circulating insulin concentrations mediate vascular-inflammatory and prothrombotic factors. However, it is unknown whether interindividual differences in circulating insulin levels are associated with different inflammatory and prothrombo...
Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models.
Sensors (Basel, Switzerland)
Jul 20, 2021
Type 1 diabetes is a chronic disease caused by the inability of the pancreas to produce insulin. Patients suffering type 1 diabetes depend on the appropriate estimation of the units of insulin they have to use in order to keep blood glucose levels in...
Generalizability of heterogeneous treatment effects based on causal forests applied to two randomized clinical trials of intensive glycemic control.
Annals of epidemiology
Jul 17, 2021
Purpose Machine learning is an attractive tool for identifying heterogeneous treatment effects (HTE) of interventions but generalizability of machine learning derived HTE remains unclear. We examined generalizability of HTE detected using causal fore...
Machine Learning to Identify Metabolic Subtypes of Obesity: A Multi-Center Study.
Frontiers in endocrinology
Jul 14, 2021
BACKGROUND AND OBJECTIVE: Clinical characteristics of obesity are heterogenous, but current classification for diagnosis is simply based on BMI or metabolic healthiness. The purpose of this study was to use machine learning to explore a more precise ...
Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study.
PloS one
Jun 24, 2021
BACKGROUND: Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ability to predict future glucose values ca...
Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.
Nature biomedical engineering
Jun 15, 2021
Regular screening for the early detection of common chronic diseases might benefit from the use of deep-learning approaches, particularly in resource-poor or remote settings. Here we show that deep-learning models can be used to identify chronic kidn...
Humans
Neural Networks, Computer
Disease Progression
Deep Learning
Blood Glucose
ROC Curve
Prospective Studies
Female
Male
Middle Aged
Body Height
Image Interpretation, Computer-Assisted
Metadata
Photography
Diabetes Mellitus, Type 2
Renal Insufficiency, Chronic
Area Under Curve
Glomerular Filtration Rate
Fundus Oculi
Body Mass Index
Body Weight
Retina
Predicting youth diabetes risk using NHANES data and machine learning.
Scientific reports
May 27, 2021
Prediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent years. However, simple questionnaire-based screening tools to reliably assess diabetes risk are only available for adults, not youth. As a first step ...
Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning.
BMC endocrine disorders
May 4, 2021
INTRODUCTION: Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and v...
Machine Learning Techniques for Hypoglycemia Prediction: Trends and Challenges.
Sensors (Basel, Switzerland)
Jan 14, 2021
(1) Background: the use of machine learning techniques for the purpose of anticipating hypoglycemia has increased considerably in the past few years. Hypoglycemia is the drop in blood glucose below critical levels in diabetic patients. This may cause...
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