AIMC Topic: Blood Glucose
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Development and Validation of a Machine Learning Model to Predict Near-Term Risk of Iatrogenic Hypoglycemia in Hospitalized Patients.
JAMA network open
Jan 4, 2021
IMPORTANCE: Accurate clinical decision support tools are needed to identify patients at risk for iatrogenic hypoglycemia, a potentially serious adverse event, throughout hospitalization.
Early Predictors of Gestational Diabetes Mellitus in IVF-Conceived Pregnancies.
Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
Dec 17, 2020
OBJECTIVE: Gestational diabetes mellitus (GDM) is associated with adverse maternal and fetal outcomes. This study aimed to identify early and reliable GDM predictors that would enable implementation of preventive and management measures.
Data-Driven Robust Control for a Closed-Loop Artificial Pancreas.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 8, 2020
We present a fully closed-loop design for an artificial pancreas (AP) that regulates the delivery of insulin for the control of Type I diabetes. Our AP controller operates in a fully automated fashion, without requiring any manual interaction with th...
Developing an Individual Glucose Prediction Model Using Recurrent Neural Network.
Sensors (Basel, Switzerland)
Nov 12, 2020
In this study, we propose a personalized glucose prediction model using deep learning for hospitalized patients who experience Type-2 diabetes. We aim for our model to assist the medical personnel who check the blood glucose and control the amount of...
[Leptin sexual dimorphism, insulin resistance, and body composition in normal weight prepubescent].
Revista chilena de pediatria
Oct 21, 2020
INTRODUCTION: The prepubertal stage is a critical period of body fat development, in which leptin and insulin re sistance has been associated, however, there are few studies in normal-weight prepubescents. Ob jective: To assess the relationship betwe...
Multi-Hour Blood Glucose Prediction in Type 1 Diabetes: A Patient-Specific Approach Using Shallow Neural Network Models.
Diabetes technology & therapeutics
Oct 13, 2020
Considering current insulin action profiles and the nature of glycemic responses to insulin, there is an acute need for longer term, accurate, blood glucose predictions to inform insulin dosing schedules and enable effective decision support for the...
Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 Diabetes.
Diabetes
Oct 6, 2020
Early and precise identification of individuals with prediabetes and type 2 diabetes (T2D) at risk for progressing to chronic kidney disease (CKD) is essential to prevent complications of diabetes. Here, we identify and evaluate prospective metabolit...
Early detection of type 2 diabetes mellitus using machine learning-based prediction models.
Scientific reports
Jul 20, 2020
Most screening tests for T2DM in use today were developed using multivariate regression methods that are often further simplified to allow transformation into a scoring formula. The increasing volume of electronically collected data opened the opport...
Deep Physiological Model for Blood Glucose Prediction in T1DM Patients.
Sensors (Basel, Switzerland)
Jul 13, 2020
Accurate estimations for the near future levels of blood glucose are crucial for Type 1 Diabetes Mellitus (T1DM) patients in order to be able to react on time and avoid hypo and hyper-glycemic episodes. Accurate predictions for blood glucose are the ...
Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors.
Sensors (Basel, Switzerland)
Jul 10, 2020
Wearable continuous glucose monitoring (CGM) sensors are revolutionizing the treatment of type 1 diabetes (T1D). These sensors provide in real-time, every 1-5 min, the current blood glucose concentration and its rate-of-change, two key pieces of info...
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