Diabetes

Latent space autoencoder generative adversarial model for retinal image synthesis and vessel segmentation.

Diabetes is a widespread condition that can lead to serious vision problems over time. Timely identification and treatment of diabetic retinopathy (DR) depend on accurately segmenting retinal vessels, which can be achieved through the invasive technique of fundus imaging. This methodology facilitates the systematic monitoring and assessment of the progression of DR. In recent years, deep learning ...

Development of an activity-based ratiometric electrochemical substrate for measuring circulating dipeptidyl peptidase-IV/CD26 in whole blood samples.

Dipeptidyl peptidase-IV (DPP-IV) is a circulating blood biomarker that diagnose pancreatic and thyroid cancers, as well as type 2 diabetes. Although current DPP-IV detection methods show promise, real-time detection in whole blood is limited, as blood samples require tedious pre-treatment. To overcome these limitations, a DPP-IV targeted electrochemical substrate, DPPLPOH (DiPeptidyl Peptidase Lat...

Comprehensive analysis of Syzygium cumini L. pomace extract as an α-amylase inhibitor: In vitro inhibition, kinetics, and computational studies.

Type 2 diabetes mellitus (T2DM) is a widespread metabolic disorder characterized by impaired regulation of blood glucose levels. Jamun (Syzygium cumin...

Agreement Between AI and Nephrologists in Addressing Common Patient Questions About Diabetic Nephropathy: Cross-Sectional Study.

This research letter presents a cross-sectional analysis comparing the agreement between artificial intelligence models and nephrologists in respondin...

Recruiting Teacher IF Modality for Nephropathy Diagnosis: A Customized Distillation Method With Attention-Based Diffusion Network.

The joint use of multiple modalities for medical image processing has been widely studied in recent years. The fusion of information from different mo...

Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy.

Anoikis and immune cell infiltration are pivotal factors in the pathophysiological mechanism of diabetic nephropathy (DN), yet a comprehensive underst...

A cascade nanoreactor based on metal azolate framework integrated natural enzyme for α-glucosidase activity assay and inhibitor screening.

Enzyme cascades have attracted widespread attention owing to the exceptional specificity and efficient signals transduction, however, constrained by t...

Artificial intelligence in retinal image analysis for hypertensive retinopathy diagnosis: a comprehensive review and perspective.

Hypertensive retinopathy (HR) occurs when the choroidal vessels, which form the photosensitive layer at the back of the eye, are injured owing to high...

GBE1 alleviates MPTP-induced PD symptoms in mice by enhancing glycolysis and oxidative phosphorylation.

In Parkinson's disease (PD), the disturbance of energy metabolism due to glucose metabolic reprogramming may be a critical factor contributing to neur...

Insulin resistance in type 1 diabetes is a key modulator of platelet hyperreactivity.

AIMS/HYPOTHESIS: Individuals with type 1 diabetes are at increased cardiovascular risk, particularly in the presence of insulin resistance. A prothrom...

A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images.

Recent advancements in deep learning have significantly impacted medical image processing domain, enabling sophisticated and accurate diagnostic tools...

Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.

Accurate prediction of post-treatment visual acuity in macular edema secondary to retinal vein occlusion (RVO-ME) is critical for optimizing anti-VEGF...

Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.

BACKGROUND AND AIMS: Low muscle mass (LMM) is a critical complication in patients with obesity and diabetes, exacerbating metabolic and cardiovascular...

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 of the modern world. Their management requires co...

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 populations. The escalating incidence of childhood ty...

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 to morbidity, mortality and healthcare burden. Desp...

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) devices for diabetic retinopathy screening and the...

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 typically requires a standardized oral glucose to...

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 first recognition during pregnancy. As a high-pre...

Prediction of Reactivation After Antivascular Endothelial Growth Factor Monotherapy for Retinopathy of Prematurity: Multimodal Machine Learning Model Study.

BACKGROUND: Retinopathy of prematurity (ROP) is the leading preventable cause of childhood blindness. A timely intravitreal injection of antivascular ...