Endocrinology

Diabetes

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

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An Extended Approach to Predict Retinopathy in Diabetic Patients Using the Genetic Algorithm and Fuzzy C-Means.

The present study is developed a new approach using a computer diagnostic method to diagnosing diabe...

Deep learning for diabetic retinopathy detection and classification based on fundus images: A review.

Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading cause of ...

Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study.

BACKGROUND: Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM...

Deep learning in diabetic foot ulcers detection: A comprehensive evaluation.

There has been a substantial amount of research involving computer methods and technology for the de...

Semi-Automated Determination of Heavy Metals in Autopsy Tissue Using Robot-Assisted Sample Preparation and ICP-MS.

The endoprosthetic care of hip and knee joints introduces multiple materials into the human body. Me...

Deep learning-based framework for the distinction of membranous nephropathy: a new approach through hyperspectral imagery.

BACKGROUND: Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopa...

Modern computational intelligence based drug repurposing for diabetes epidemic.

BACKGROUND AND AIM: Objectives are to explore recent advances in discovery of new antidiabetic agent...

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.

Regular screening for the early detection of common chronic diseases might benefit from the use of d...

Novel deep learning-based transcriptome data analysis for drug-drug interaction prediction with an application in diabetes.

BACKGROUND: Drug-drug interaction (DDI) is a serious public health issue. The L1000 database of the ...

A novel stacking technique for prediction of diabetes.

BACKGROUND: Machine Learning (ML) represents a rapidly growing technology that supplies the most eff...

Decoding empagliflozin's molecular mechanism of action in heart failure with preserved ejection fraction using artificial intelligence.

The use of sodium-glucose co-transporter 2 inhibitors to treat heart failure with preserved ejection...

Hemorrhage Detection Based on 3D CNN Deep Learning Framework and Feature Fusion for Evaluating Retinal Abnormality in Diabetic Patients.

Diabetic retinopathy (DR) is the main cause of blindness in diabetic patients. Early and accurate di...

Multiclass wound image classification using an ensemble deep CNN-based classifier.

Acute and chronic wounds are a challenge to healthcare systems around the world and affect many peop...

Functional link convolutional neural network for the classification of diabetes mellitus.

Diabetes is a faction of metabolic ailments distinguished by hyperglycemia which is the consequence ...

An Effective Method for Detecting and Classifying Diabetic Retinopathy Lesions Based on Deep Learning.

Diabetic retinopathy occurs as a result of the harmful effects of diabetes on the eyes. Diabetic ret...

A deep learning system for detecting diabetic retinopathy across the disease spectrum.

Retinal screening contributes to early detection of diabetic retinopathy and timely treatment. To fa...

Predicting youth diabetes risk using NHANES data and machine learning.

Prediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent ...

Diabetic Retinopathy Fundus Image Classification and Lesions Localization System Using Deep Learning.

Diabetic retinopathy (DR) is a disease resulting from diabetes complications, causing non-reversible...

An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived from , Decreases HbA1c in a Prediabetic Population.

The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for indi...

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