Endocrinology

Diabetes

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

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Is handling unbalanced datasets for machine learning uplifts system performance?: A case of diabetic prediction.

BACKGROUND AND AIMS: Healthcare is a sensitive sector, and addressing the class imbalance in the hea...

IDA-MIL: Classification of Glomerular with Spike-like Projections via Multiple Instance Learning with Instance-level Data Augmentation.

BACKGROUND AND OBJECTIVE: Tiny spike-like projections on the basement membrane of glomeruli are the ...

Bridging the resources gap: deep learning for fluorescein angiography and optical coherence tomography macular thickness map image translation.

BACKGROUND: To assess the ability of the pix2pix generative adversarial network (pix2pix GAN) to syn...

Novel Internet of Things based approach toward diabetes prediction using deep learning models.

The integration of the Internet of Things with machine learning in different disciplines has benefit...

Diabetic retinopathy screening using deep learning for multi-class imbalanced datasets.

Screening and diagnosis of diabetic retinopathy disease is a well known problem in the biomedical do...

Deep learning fuzzy immersion and invariance control for type-I diabetes.

In this study, a novel approach is proposed for glucose regulation in type-I diabetes patients. Unli...

Feasibility Study of Constructing a Screening Tool for Adolescent Diabetes Detection Applying Machine Learning Methods.

Prediabetes and diabetes are becoming alarmingly prevalent among adolescents over the past decade. H...

Liver enzymes, alcohol consumption and the risk of diabetes: the Suita study.

AIM: We aimed to investigate the combined impact of liver enzymes and alcohol consumption on the dia...

Characterization of the SGLT2 Interaction Network and Its Regulation by SGLT2 Inhibitors: A Bioinformatic Analysis.

Sodium-glucose cotransporter 2 (SGLT2), also known as solute carrier family 5 member 2 (SLC5A2), is...

A Deep Learning Model Incorporating Knowledge Representation Vectors and Its Application in Diabetes Prediction.

The deep learning methods for various disease prediction tasks have become very effective and even s...

Robust Fovea Detection in Retinal OCT Imaging Using Deep Learning.

The fovea centralis is an essential landmark in the retina where the photoreceptor layer is entirely...

Semi-supervised classification of fundus images combined with CNN and GCN.

PURPOSE: Diabetic retinopathy (DR) is one of the most serious complications of diabetes, which is a ...

A comprehensive review of methods based on deep learning for diabetes-related foot ulcers.

BACKGROUND: Diabetes mellitus (DM) is a chronic disease with hyperglycemia. If not treated in time, ...

Diagnosing Diabetic Retinopathy in OCTA Images Based on Multilevel Information Fusion Using a Deep Learning Framework.

OBJECTIVE: As an extension of optical coherence tomography (OCT), optical coherence tomographic angi...

Gray wolf optimization-extreme learning machine approach for diabetic retinopathy detection.

Many works have employed Machine Learning (ML) techniques in the detection of Diabetic Retinopathy (...

Automated multidimensional deep learning platform for referable diabetic retinopathy detection: a multicentre, retrospective study.

OBJECTIVE: To develop and validate a real-world screening, guideline-based deep learning (DL) system...

Automated Prediction of Kidney Failure in IgA Nephropathy with Deep Learning from Biopsy Images.

BACKGROUND AND OBJECTIVES: Digital pathology and artificial intelligence offer new opportunities for...

Identifying endotypes of individuals after an attack of pancreatitis based on unsupervised machine learning of multiplex cytokine profiles.

After an attack of pancreatitis, individuals may develop metabolic sequelae (eg, new-onset diabetes)...

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