Diabetes

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 estimating the risk of diabetes is glycated hemoglobin (HbA1c). Early risk assessment and intervention techniques can be improved by identifying important clinical and demographic variables. Through the integration of clinical indicators (lipid profiles, albumin, and liver enzymes) and demographic char...

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 accurately predicting the risk of postoperative vitreous cavity haemorrhage (POVCH) following vitrectomy with intraocular pharmacotherapy in patients with proliferative diabetic retinopathy (PDR). METHODS: This retrospective study included patients with PDR who underwent vitrectomy combined with in...

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 optimizing type 2 diabetes outcomes. Using data from...

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 management team (DMT) review reduces EUR. While glu...

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 cause of blindness. Early diagnose of diabetic ret...

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 strength of type D personality and allostatic load...

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 in children with type 1 diabetes mellitus (T1DM) an...

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 prospective diagnostic accuracy is not well defin...

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 plaques and tau neurofibrillary tangles, with tau path...

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 screening adrenal gland volume abnormalities and est...

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 premature infants and a leading cause of preventabl...

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 with high mortality risks. This study aims to devel...

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 worldwide, a number projected to rise to 1.3 billion by 2...

C-peptide Index under Non-fasting Conditions Can Predict the Likelihood of Future Insulin Therapy in Outpatients with Type 2 Diabetes Mellitus Not Receiving Insulin at Baseline.

Objective This study aimed to develop a clinical model in which the C-peptide index (CPI) under non-fasting conditions can predict future insulin ther...

Drug Repurposing in Oncology: A Strategic Pathway to Unlocking New Therapeutic Potential.

The growing number of cancer cases and deaths highlights the urgent need for innovative treatment approaches. One technique that has lately been recog...

Development of a Contraction Force Control Method for Bioactuators Using a Muscle Contraction Model.

Bioactuators consisting of cultured skeletal muscle and an artificial lattice have not only the same flexibility as soft actuators but also the same b...

Investigation of biochemical alterations in the brain of db/db diabetic mice using integrated FTIR and Raman spectroscopy combined with machine learning.

This study systematically analyzed the molecular metabolic alterations in the brain tissue of type 2 diabetic mice at different disease stages by inte...

The use of machine learning to predict pharmacological therapy in gestational diabetes: A scoping review.

AIMS: Early identification of pharmacological therapy for gestational diabetes mellitus (GDM), a common pregnancy complication, through machine learni...

Diverse combination of factors associated with the development of diabetic kidney disease among data-driven diabetes subtypes: analysis of the J-DREAMS registry.

AIMS/HYPOTHESIS: Available methods for predicting the onset and progression of diabetic kidney disease (DKD) and end-stage kidney disease (ESKD) are n...

Artificial intelligence-driven clinical decision support systems to assist healthcare professionals and people with diabetes in Europe at the point of care: a Delphi-based consensus roadmap.

The use of artificial intelligence (AI) to improve the diagnosis, assessment and treatment of people with diabetes has the potential to drive a paradi...