Diabetes

The efficacy of CGM driven machine learning algorithms in predicting hypoglycemia in patients with T1DM: a systematic review and meta-analysis.

PURPOSE: An important function of continuous glucose monitoring (CGM) is to alert individuals with t...

Comments on: "Artificial intelligence improves survival decision-making in diabetic emergencies: A cross-sectional study".

Literature-informed ensemble machine learning for three-year diabetic kidney disease risk prediction in type 2 diabetes: Development, validation, and deployment of the PSMMC NephraRisk model.

INTRODUCTION: Diabetic kidney disease (DKD) and diabetic nephropathy (DN) affect around 40% of diabe...

Synergistic impact of insulin resistance and hepatic fibrosis on cardiovascular events in patients with coronary artery disease: A machine learning subtyping and interaction analysis.

BACKGROUND AND AIMS: Insulin resistance (IR) and hepatic fibrosis are significant yet underexplored ...

Automated Feature Segmentation of Ultra-Widefield OCT Images.

OBJECTIVE OR PURPOSE: To develop a lightweight neural network for automated cross-sectional and en f...

AI-powered literature mining reveals the therapeutic significance of GLP-1 receptor: Simulation of natural agonist candidates based on molecular dynamics.

Glucagon-like peptide-1 (GLP-1), a pivotal incretin hormone modulating glycemic homeostasis, has eme...

Explainable machine learning-driven predictive modelling of incident cognitive impairment in individuals with early-stage cardiovascular-kidney-metabolic syndrome: Insights from a longitudinal CHARLS cohort study.

AIMS: While cardiovascular-kidney-metabolic (CKM) syndrome has been recognised as a continuum of int...

Clinical utility of an AI-based retinal imaging model for cardiovascular risk prediction in hypertensive retinopathy.

OBJECTIVE: This study presents an independent clinical evaluation of Dr.Noon CVD, a commercially dev...

Machine learning-based binary classification of elevated HbA1c (≥6.5 %) for risk assessment.

OBJECTIVE: One of the most important biomarkers for evaluating long-term glycemic management and est...

Prediction model for the risk of vitreous haemorrhage after vitrectomy combined with intraocular injection for the treatment of proliferative diabetic retinopathy.

OBJECTIVE: The purpose of this study was to develop a lightweight multimodal deep learning model for...

Predictors of glycemic control with imeglimin for type 2 diabetes: Results of machine learning analyses using clinical trial data.

INTRODUCTION: Identifying patient characteristics predictive of treatment response is crucial for op...

Early, unplanned readmission in diabetes inpatients: Comparing the utility and performance of machine learning and traditional prediction models to guide timely diabetes management team review.

BACKGROUND: Inpatients with diabetes have higher early unplanned readmission (EUR) rates. Diabetes m...

SODAS: Second-order optimization differential architecture search for diabetic retinopathy prediction.

Diabetic retinopathy, which is a retinal disease that results from diabetes, has become the leading ...

Joint Associations of Type D Personality and Allostatic Load With Coronary Artery Disease in Type 2 Diabetes: Evaluating the Role of Allostatic Load.

OBJECTIVE: This study aimed to (1) evaluate and compare the independent associations and predictive ...

Gut microbiome profiles and associated functional pathways are linked to Mediterranean diet adherence and blood glucose control in adults with type 1 diabetes mellitus.

BACKGROUND AND AIMS: The Mediterranean diet (MD) has been associated with better glycaemic control i...

Prospective validation of deep-learning algorithms for diabetic retinopathy screening: A systematic review and meta-analysis.

Deep-learning (DL) algorithms are widely promoted for diabetic-retinopathy (DR) screening, yet their...

Diabetes-linked metabolic dysfunction relates with distinct tau phosphorylation patterns, neuroinflammation and cognitive impairment in mouse models of Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-β plaq...

Personalized adrenal gland volume reference ranges and development of a fully automated deep learning screening tool.

OBJECTIVE: This study aims to develop a low-dose CT-based, fully automated deep learning tool for sc...

Perspectives on screening in retinopathy of prematurity: new algorithms and AI tools.

Retinopathy of prematurity (ROP) is a vasoproliferative blinding disorder of the retina, unique to p...

Development and validation of a machine learning model to predict 30-day mortality in ischemic stroke patients with consciousness impairment: Insights from MIMIC-IV database and multicenter ICU data in China.

BACKGROUND: Patients with ischemic stroke complicated by consciousness disorders remain associated w...

Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.

Type 2 diabetes is a polygenic, heterogeneous disease affecting over 530 million individuals worldwi...