Endocrinology

Diabetes

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

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Predictive models and determinants of mortality among T2DM patients in a tertiary hospital in Ghana, how do machine learning techniques perform?

BACKGROUND: The increasing prevalence of type 2 diabetes mellitus (T2DM) in lower and middle - incom...

Deep learning model for automatic detection of different types of microaneurysms in diabetic retinopathy.

PURPOSE: This study aims to develop a deep-learning-based software capable of detecting and differen...

A machine learning model accurately identifies glycogen storage disease Ia patients based on plasma acylcarnitine profiles.

BACKGROUND: Glycogen storage disease (GSD) Ia is an ultra-rare inherited disorder of carbohydrate me...

Color fundus photograph-based diabetic retinopathy grading via label relaxed collaborative learning on deep features and radiomics features.

INTRODUCTION: Diabetic retinopathy (DR) has long been recognized as a common complication of diabete...

Machine learning and molecular dynamics simulations predict potential TGR5 agonists for type 2 diabetes treatment.

INTRODUCTION: Treatment of type 2 diabetes (T2D) remains a significant challenge because of its mult...

The effect of renal function on the clinical outcomes and management of patients hospitalized with hyperglycemic crises.

BACKGROUND: The global prevalence of diabetes has been rising rapidly in recent years, leading to an...

Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches.

Deep learning-based medical image analysis has shown strong potential in disease categorization, seg...

Exploring the effect of gestational diabetes mellitus on retinal vascular morphology by PKSEA-Net.

BACKGROUND: Gestational diabetes mellitus (GDM) is a temporary metabolic disorder in which small ret...

Adversarial Exposure Attack on Diabetic Retinopathy Imagery Grading.

Diabetic Retinopathy (DR) is a leading cause of vision loss around the world. To help diagnose it, n...

Robust predictive framework for diabetes classification using optimized machine learning on imbalanced datasets.

INTRODUCTION: Diabetes prediction using clinical datasets is crucial for medical data analysis. Howe...

A data-driven machine learning algorithm to predict the effectiveness of inulin intervention against type II diabetes.

INTRODUCTION: The incidence of type 2 diabetes mellitus (T2DM) has increased in recent years. Alongs...

Empirical analysis on retinal segmentation using PSO-based thresholding in diabetic retinopathy grading.

OBJECTIVES: Diabetic retinopathy (DR) is associated with long-term diabetes and is a leading cause o...

Predicting and Ranking Diabetic Ketoacidosis Risk Among Youth with Type 1 Diabetes with a Clinic-to-Clinic Transferrable Machine Learning Model.

To use electronic health record (EHR) data to develop a scalable and transferrable model to predict...

A novel RFE-GRU model for diabetes classification using PIMA Indian dataset.

Diabetes is a long-term condition characterized by elevated blood sugar levels. It can lead to a var...

Lesion classification and diabetic retinopathy grading by integrating softmax and pooling operators into vision transformer.

INTRODUCTION: Diabetic retinopathy grading plays a vital role in the diagnosis and treatment of pati...

Curcumin nanocrystals ameliorate ferroptosis of diabetic nephropathy through glutathione peroxidase 4.

OBJECTIVE: The aim of this study was to investigate the effect of curcumin nanocrystals (Cur-NCs) on...

mCNN-glucose: Identifying families of glucose transporters using a deep convolutional neural network based on multiple-scanning windows.

Glucose transporters are essential carrier proteins that function on the phospholipid bilayer to fac...

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