Diabetes

Artificial Intelligence Improves Patient Follow-Up in a Diabetic Retinopathy Screening Program.

PURPOSE: We examine the rate of and reasons for follow-up in an Artificial Intelligence (AI)-based w...

Integration of Deep Learning and Sequential Metabolism to Rapidly Screen Dipeptidyl Peptidase (DPP)-IV Inhibitors from .

Traditional Chinese medicine (TCM) possesses unique advantages in the management of blood glucose an...

Effectiveness of Nicotinamide Phosphoribosyltransferase/Pre-B Cell Colony-enhancing Factor/Visfatin in preventing High Glucose-induced Neurotoxicity in an In-vitro Model of Diabetic Neuropathy.

INTRODUCTION: Diabetic neuropathy is a well-known complication of diabetes. Recently, hyperglycemia-...

Risk prediction models for postpartum glucose intolerance in women with a history of gestational diabetes mellitus: a scoping review.

OBJECTIVE: The objective of this scoping review was to investigate the effectiveness and limitations...

Assessing Elevated Blood Glucose Levels Through Blood Glucose Evaluation and Monitoring Using Machine Learning and Wearable Photoplethysmography Sensors: Algorithm Development and Validation.

BACKGROUND: Diabetes mellitus is the most challenging and fastest-growing global public health conce...

Discovery of type 2 diabetes mellitus with correlation and optimization driven hybrid deep learning approach.

Diabetes mellitus is a severe condition that has the potential to impair strength. The disease known...

Insulin signaling in insulin-dysregulated Icelandic horses.

The underlying molecular mechanisms leading to insulin dysregulation are poorly understood in horses...

Development of a novel combined nomogram model integrating deep learning radiomics to diagnose IgA nephropathy clinically.

This study aimed to develop and validate a combined nomogram model based on superb microvascular ima...

Predicting of diabetic retinopathy development stages of fundus images using deep learning based on combined features.

The number of diabetic retinopathy (DR) patients is increasing every year, and this causes a public ...

Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo.

Single-cell analysis in living humans is essential for understanding disease mechanisms, but it is i...

Electroencephalographic abnormalities in children with type 1 diabetes mellitus: a prospective study.

BACKGROUND/AIM: The aim herein was to investigate epileptiform discharges on electroencephalogram (E...

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges.

The increasing prevalence of diabetes, high avoidable morbidity and mortality due to diabetes and di...

An effective correlation-based data modeling framework for automatic diabetes prediction using machine and deep learning techniques.

The rising risk of diabetes, particularly in emerging countries, highlights the importance of early ...

Development of an automated estimation of foot process width using deep learning in kidney biopsies from patients with Fabry, minimal change, and diabetic kidney diseases.

Podocyte injury plays a key role in pathogenesis of many kidney diseases with increased podocyte foo...

Osteoporosis in Adrenal Insufficiency: Could Metformin be Protective?

Adrenal insufficiency (AI) is a serious disorder characterized by the adrenal glucocorticoid deficie...

Diagnosis of diabetes mellitus using high frequency ultrasound and convolutional neural network.

The incidence of diabetes mellitus has been increasing, prompting the search for non-invasive diagno...

Application of serum SERS technology combined with deep learning algorithm in the rapid diagnosis of immune diseases and chronic kidney disease.

Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic dete...

Clinical Implementation of Autonomous Artificial Intelligence Systems for Diabetic Eye Exams: Considerations for Success.

As artificial intelligence goes multimodal, medical applications multiply.

Machines don't have eyes, but you wouldn't know that if you followed the progression of deep learnin...

Performance and limitations of a supervised deep learning approach for the histopathological Oxford Classification of glomeruli with IgA nephropathy.

BACKGROUND AND OBJECTIVE: The Oxford Classification for IgA nephropathy is the most successful examp...

Deep Transfer Learning-Based Approach for Glucose Transporter-1 (GLUT1) Expression Assessment.

Glucose transporter-1 (GLUT-1) expression level is a biomarker of tumour hypoxia condition in immuno...