AIMC Topic: Insulin

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Which surrogate insulin resistance indices best predict coronary artery disease? A machine learning approach.

Cardiovascular diabetology
BACKGROUND: Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as...

Neuro-fuzzy model for predicting insulin delivery from crosslinked agar-carbomer hydrogels.

Computer methods in biomechanics and biomedical engineering
This study focuses on the innovation of an inhaled sustained release form of insulin and the development of a neuro-fuzzy model specifically tailored to predict insulin release kinetics from polycondensed agar-carbomer hydrogels. These were synthesiz...

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...

Application of machine learning in affordable and accessible insulin management for type 1 and 2 diabetes: A comprehensive review.

Artificial intelligence in medicine
Proper insulin management is vital for maintaining stable blood sugar levels and preventing complications associated with diabetes. However, the soaring costs of insulin present significant challenges to ensuring affordable management. This paper con...

The association of serum irisin with anthropometric, metabolic, and bone parameters in obese children and adolescents.

Frontiers in endocrinology
BACKGROUND: Irisin is an adipomyokine secreted by muscle and adipose cells, and it plays a role in glucose, fat, and bone metabolism. This study aimed to determine the correlation of serum irisin levels with anthropometric, metabolic, and bone parame...

Time for Using Machine Learning for Dose Guidance in Titration of People With Type 2 Diabetes? A Systematic Review of Basal Insulin Dose Guidance.

Journal of diabetes science and technology
BACKGROUND: Real-world studies of people with type 2 diabetes (T2D) have shown insufficient dose adjustment during basal insulin titration in clinical practice leading to suboptimal treatment. Thus, 60% of people with T2D treated with insulin do not ...

Deep learning fuzzy immersion and invariance control for type-I diabetes.

Computers in biology and medicine
In this study, a novel approach is proposed for glucose regulation in type-I diabetes patients. Unlike most studies, the glucose-insulin metabolism is considered to be uncertain. A new approach on the basis of the Immersion and Invariance (I&I) theor...

Autonomous push button-controlled rapid insulin release from a piezoelectrically activated subcutaneous cell implant.

Science advances
Traceless physical cues are desirable for remote control of the in situ production and real-time dosing of biopharmaceuticals in cell-based therapies. However, current optogenetic, magnetogenetic, or electrogenetic devices require sophisticated elect...

Dietary administration of D-chiro-inositol attenuates sex-specific metabolic imbalances in the 5xFAD mouse model of Alzheimer's disease.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Increasing evidence shows that hypothalamic dysfunction, insulin resistance, and weight loss precede and progress along with the cognitive decline in sporadic Alzheimer's Disease (AD) with sex differences. This study aimed to determine the effect of ...

A Deep Learning Framework for Automatic Meal Detection and Estimation in Artificial Pancreas Systems.

Sensors (Basel, Switzerland)
Current artificial pancreas (AP) systems are hybrid closed-loop systems that require manual meal announcements to manage postprandial glucose control effectively. This poses a cognitive burden and challenge to users with T1D since this relies on freq...