Diabetes

Structural Insights into the Substrate Egress Pathways Explains Specificity and Inhibition of Human Glucose Transporters (GLUT1 and GLUT9).

Glucose transporters (GLUTs) play critical roles in cellular energy homeostasis and substrate-specific transport. Dysfunctional mutations can cause GLUT1 deficiency syndrome, and excessive expression of GLUT1 is linked to cancer progression, while abnormal regulation of urate transport by GLUT9 is associated with hyperuricemia and gout. In this study, machine-learning-driven molecular dynamics sim...

Development of a machine learning model for predicting cardiovascular risk factors and major adverse cardiovascular events in young adults with glucose metabolism disorders.

BACKGROUND: Glucose metabolism disorders (GMDs) are a serious global public health issue, characterized by a high incidence rate and youthfulness. GMDs contribute to the occurrence of major adverse cardiovascular events (MACEs), meanwhile with the rest of the remaining cardiovascular risk factors (CVRFs) act synergistically to influence MACEs. Although numerous studies have explored CVRFs and thei...

Prediction of Insulin Resistance in Nondiabetic Population Using LightGBM and Cohort Validation of Its Clinical Value: Cross-Sectional and Retrospective Cohort Study.

BACKGROUND: Insulin resistance (IR), a precursor to type 2 diabetes and a major risk factor for various chronic diseases, is becoming increasingly pre...

Implementing an artificial intelligence system into a diabetic eye screening programme in Tanzania.

Tanzania has the highest age-adjusted prevalence of diabetes in sub-Saharan Africa. Diabetic retinopathy, a common complication, is a significant caus...

AI Quantification of Vascular Lesions in Mouse Fundus Fluorescein Angiography.

PURPOSE: Quantifying vascular leakage in fundus fluorescein angiography (FFA) is a critical endpoint in preclinical models of diseases such as neovasc...

Modulation of insulin aggregation by betaine and proline directly observed via real-time super-resolution microscopy.

Protein aggregation is associated with a spectrum of neurodegenerative diseases. Although many small ligands have been found to modulate or inhibit pr...

A prognostic model of immunoglobulin A nephropathy using artificial neural network: a retrospective study based on integrated Chinese and Western Medicine.

OBJECTIVE: To establish and evaluate a prognostic model of immunoglobulin A nephropathy (IgAN) based on integrated Chinese and Western Medicine.

Vision transformer-based stratification of pre/diabetic and pre/hypertensive patients from retinal photographs for 3PM applications.

OBJECTIVE: Diabetes and hypertension pose significant health risks, especially when poorly managed. Retinal evaluation though fundus photography can p...

CGMformer: a novel deep-learning model promising for early detection of prediabetes to effectively prevent type 2 diabetes.

KDELR3 and YOD1 proteins as critical endoplasmic reticulum stress mediators and potential therapeutic targets in diabetic foot ulcers: An integrated bioinformatics analysis.

BACKGROUND: Diabetic foot ulcers (DFU) represent one of the most severe complications of diabetes mellitus and are closely associated with persistent ...

Explainable machine learning model incorporating social determinants of health to predict chronic kidney disease in type 2 diabetes patients.

BACKGROUND AND OBJECTIVES: Social determinants of health (SDOH) play a critical role in the onset and progression of chronic kidney disease (CKD). Des...

MCD-LightGBM System for Intelligent Analyzing Heterogeneous Clinical Drug Therapeutic Effects.

Causal effect estimation of individual heterogeneity is a core issue in the field of causal inference, and its application in medicine poses an active...

SNER: Semi-Supervised Named Entity Recognition for Large Volume of Diabetes Data.

The medical literature and records on diabetes provide crucial resources for diabetes prevention and treatment. However, extracting entities from thes...

Eigenhearts: Cardiac diseases classification using eigenfaces approach.

In the realm of cardiovascular medicine, medical imaging plays a crucial role in accurately classifying cardiac diseases and making precise diagnoses....

An enhanced harmonic densely connected hybrid transformer network architecture for chronic wound segmentation utilising multi-colour space tensor merging.

Chronic wounds and associated complications present ever growing burdens for clinics and hospitals world wide. Venous, arterial, diabetic, and pressur...

IR-MBiTCN: Computational prediction of insulin receptor using deep learning: A multi-information fusion approach with multiscale bidirectional temporal convolutional network.

The insulin receptor (IR) is a transmembrane protein that controls glucose homeostasis and is highly associated with chronic diseases including cancer...

A dynamic model using k-NN algorithm for predicting diabetes and breast cancer.

Healthcare remains a critical focus due to its direct impact on human well-being. Diabetes, currently the fastest-growing chronic disease globally, po...

Machine Learning Insights Into Amputation Risk: Evaluating Wound Classification Systems in Diabetic Foot Ulcers.

This study compares the performance of various wound classification systems to determine which system most effectively predicts amputation risk in dia...

Global-Local Transformer Network for Automatic Retinal Pathological Fluid Segmentation in Optical Coherence Tomography Images.

BACKGROUND AND OBJECTIVE: As a pivotal biomarker, the accurate segmentation of retinal pathological fluid such as intraretinal fluid (IRF), subretinal...

Deep reinforcement learning for Type 1 Diabetes: Dual PPO controller for personalized insulin management.

BACKGROUND: Managing blood glucose levels in Type 1 Diabetes Mellitus (T1DM) is essential to prevent complications. Traditional insulin delivery metho...