Endocrinology

Diabetes

Latest AI and machine learning research in diabetes for healthcare professionals.

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Managing chronic disease in the digital era: The role of telemedicine apps and platforms.

Chronic diseases such as diabetes, heart disease, or asthma are one of the biggest health challenges...

Modeling the number of new cases of childhood type 1 diabetes using Poisson regression and machine learning methods; a case study in Saudi Arabia.

Diabetes mellitus stands out as one of the most prevalent chronic conditions affecting pediatric pop...

Advancing Cardiovascular, Kidney, and Metabolic Medicine: A Narrative Review of Insights and Innovations for the Future.

Cardiovascular, kidney and metabolic (CKM) conditions are interrelated, significantly contributing t...

SEM model analysis of diabetic patients' acceptance of artificial intelligence for diabetic retinopathy.

AIMS: This study aimed to investigate diabetic patients' acceptance of artificial intelligence (AI) ...

Predicting isolated impaired glucose tolerance without oral glucose tolerance test using machine learning in Chinese Han men.

BACKGROUND: Isolated Impaired Glucose Tolerance (I-IGT) represents a specific prediabetic state that...

GDM-BC: Non-invasive body composition dataset for intelligent prediction of Gestational Diabetes Mellitus.

Gestational Diabetes Mellitus (GDM) refers to any degree of impaired glucose tolerance with onset or...

Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks.

Diabetic Retinopathy (DR) is a leading cause of vision impairment globally, necessitating regular sc...

The association of trimethylamine N-oxide with diabetic retinopathy Pathology: Insights from network toxicology and molecular docking analysis.

Trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite, has emerged as a potential contr...

Diabetic retinopathy detection based on mobile maxout network and weber local descriptor feature selection using retinal fundus image.

Retinal screening provides for earlier detection of diabetic retinopathy (DR) as well as prompt diag...

A novel deep learning approach to classify 3D foot types of diabetic patients.

Diabetes mellitus is a worldwide epidemic that leads to significant changes in foot shape, deformiti...

Comparison of artificial intelligence-generated and physician-generated patient education materials on early diabetic kidney disease.

BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetes mellitus ...

Computational modelling for risk assessment of neurological disorder in diabetes using Hodgkin-Huxley model.

BACKGROUND: Diabetes mellitus, characterized by chronic glucose dysregulation, significantly increas...

Sharper insights: Adaptive ellipse-template for robust fovea localization in challenging retinal landscapes.

Automated identification of retinal landmarks, particularly the fovea is crucial for diagnosing diab...

Two-stage color fundus image registration via Keypoint Refinement and Confidence-Guided Estimation.

Color fundus images are widely used for diagnosing diseases such as Glaucoma, Cataracts, and Diabeti...

Coptidis rhizoma and berberine as anti-cancer drugs: A 10-year updates and future perspectives.

Cancer continues to be among the most substantial health challenges globally. Among various natural ...

Machine Learning Models for Predicting Type 2 Diabetes Complications in Malaysia.

This study aimed to develop machine learning (ML) models to predict diabetic complications in patien...

Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.

This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differe...

Assessing the association of multi-environmental chemical exposures on metabolic syndrome: A machine learning approach.

Metabolic syndrome (MetS) is a major global public health concern due to its rising prevalence and a...

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