AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Insulin

Showing 21 to 30 of 104 articles

Clear Filters

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
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...

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 ...

Machine Learning to Identify Metabolic Subtypes of Obesity: A Multi-Center Study.

Frontiers in endocrinology
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 ...

Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models.

Sensors (Basel, Switzerland)
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...

Magneto-Responsive Microneedle Robots for Intestinal Macromolecule Delivery.

Advanced materials (Deerfield Beach, Fla.)
Oral administration is the most convenient and commonly used approach for drug delivery, while it is still a challenge to overcome the complicated gastrointestinal barriers and realize efficient macromolecular drug absorption. Here, novel magneto-res...

Machine learning for initial insulin estimation in hospitalized patients.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to determine whether machine learning can predict initial inpatient total daily dose (TDD) of insulin from electronic health records more accurately than existing guideline-based dosing recommendations.

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...

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...

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...

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 ...