AIMC Topic: Blood Glucose

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Explainable hypoglycemia prediction models through dynamic structured grammatical evolution.

Scientific reports
Effective blood glucose management is crucial for people with diabetes to avoid acute complications. Predicting extreme values accurately and in a timely manner is of vital importance to them. People with diabetes are particularly concerned about suf...

A Scalable Application of Artificial Intelligence-Driven Insulin Titration Program to Transform Type 2 Diabetes Management.

Diabetes technology & therapeutics
Despite new pharmacotherapy, most patients with long-term type 2 diabetes are still hyperglycemic. This could have been solved by insulin with its unlimited potential efficacy, but its dynamic physiology demands frequent titrations which are overdem...

Development and Validation of a Machine Learning Model to Predict Weekly Risk of Hypoglycemia in Patients with Type 1 Diabetes Based on Continuous Glucose Monitoring.

Diabetes technology & therapeutics
The aim of this study was to develop and validate a prediction model based on continuous glucose monitoring (CGM) data to identify a week-to-week risk profile of excessive hypoglycemia. We analyzed, trained, and internally tested two prediction mod...

DDLA: a double deep latent autoencoder for diabetic retinopathy diagnose based on continuous glucose sensors.

Medical & biological engineering & computing
The current diagnosis of diabetic retinopathy is based on fundus images and clinical experience. However, considering the ineffectiveness and non-portability of medical devices, we aimed to develop a diagnostic model for diabetic retinopathy based on...

Using Artificial Intelligence to Improve the Accuracy of a Wrist-Worn, Noninvasive Glucose Monitor: A Pilot Study.

Journal of diabetes science and technology
BACKGROUND: Self-monitoring of glucose is important to the successful management of diabetes; however, existing monitoring methods require a degree of invasive measurement which can be unpleasant for users. This study investigates the accuracy of a n...

Predictive modeling of multi-class diabetes mellitus using machine learning and filtering iraqi diabetes data dynamics.

PloS one
Diabetes is a persistent metabolic disorder linked to elevated levels of blood glucose, commonly referred to as blood sugar. This condition can have detrimental effects on the heart, blood vessels, eyes, kidneys, and nerves as time passes. It is a ch...

Pre-hospital glycemia as a biomarker for in-hospital all-cause mortality in diabetic patients - a pilot study.

Cardiovascular diabetology
BACKGROUND: Type 2 Diabetes Mellitus (T2DM) presents a significant healthcare challenge, with considerable economic ramifications. While blood glucose management and long-term metabolic target setting for home care and outpatient treatment follow est...

Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial neural networks (ANNs) are showing promising results for reliable glucose predictions, offering timely warnings for glucose fluctuations. The transla...

Progression from Prediabetes to Diabetes in a Diverse U.S. Population: A Machine Learning Model.

Diabetes technology & therapeutics
To date, there are no widely implemented machine learning (ML) models that predict progression from prediabetes to diabetes. Addressing this knowledge gap would aid in identifying at-risk patients within this heterogeneous population who may benefit...