Diabetes

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 diabetic diseases with the use of fluorescein images. In doing so, this study presented the growth region algorithm for the aim of diagnosing diabetes, considering the angiography images of the patients' eyes. In addition, this study integrated two methods, including fuzzy C-means (FCM) and genetic algor...

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 blindness globally. Early detection and treatment are necessary in order to delay or avoid vision deterioration and vision loss. To that end, many artificial-intelligence-powered methods have been proposed by the research community for the detection and classification of diabetic retinopathy on fund...

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) and algorithms that continuously guide insulin d...

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 detection and recognition of diabetic foot ulcers (D...

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. Metal containing implant surfaces release degradatio...

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 idiopathic membranous nephropathy (IMN) and hepatitis B ...

Modern computational intelligence based drug repurposing for diabetes epidemic.

BACKGROUND AND AIM: Objectives are to explore recent advances in discovery of new antidiabetic agents using repurposing strategies and to discuss mode...

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 deep-learning approaches, particularly in resource-...

A novel stacking technique for prediction of diabetes.

BACKGROUND: Machine Learning (ML) represents a rapidly growing technology that supplies the most effective solutions for solving complex problems. The...

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 fraction (HFpEF) is under investigation in ongoin...

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 diagnosis can improve the analysis and prognosis of ...

Automated AI labeling of optic nerve head enables insights into cross-ancestry glaucoma risk and genetic discovery in >280,000 images from UKB and CLSA.

Cupping of the optic nerve head, a highly heritable trait, is a hallmark of glaucomatous optic neuropathy. Two key parameters are vertical cup-to-disc...

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 people's lives annually. Wound classification is a key...

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 of a defect, in the action of insulin, insulin sec...

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 retinopathy is also a disease that should be diagnose...

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 facilitate the screening process, we develop a deep ...

Predicting youth diabetes risk using NHANES data and machine learning.

Prediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent years. However, simple questionnaire-based screeni...

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 damage to retina blood vessels. DR is a leading c...

Classification and Prediction on the Effects of Nutritional Intake on Overweight/Obesity, Dyslipidemia, Hypertension and Type 2 Diabetes Mellitus Using Deep Learning Model: 4-7th Korea National Health and Nutrition Examination Survey.

Few studies have been conducted to classify and predict the influence of nutritional intake on overweight/obesity, dyslipidemia, hypertension and type...

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 individuals to develop type 2 diabetes and associated ...