Diabetes

A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy.

The main complication of diabetes is Diabetic retinopathy (DR), retinal vascular disease and it leads to the blindness. Regular screening for early DR disease detection is considered as an intensive labor and resource oriented task. Therefore, automatic detection of DR diseases is performed only by using the computational technique is the great solution. An automatic method is more reliable to det...

Inhibitory activity of phenolic-rich pistachio green hull extract-enriched pasta on key type 2 diabetes relevant enzymes and glycemic index.

Phenolic compounds as agro-industrial by-products have been associated with health benefits since they exhibit high antioxidant activity and anti-diabetic properties. In this study, polyphenol-rich extract from pistachio green hull (PGH) was evaluated for antioxidant activity and its ability to inhibit α-amylase and α-glucosidase activity in vitro. The effect of PGH extract powder on in vitro star...

A Successful Approach to Kidney Transplantation in Patients With Enteric (Secondary) Hyperoxaluria.

BACKGROUND: Enteric hyperoxaluria due to malabsorption may cause chronic oxalate nephropathy and lead to end-stage renal disease. Kidney transplantati...

Synthesis and characterization of ZnO phytonanocomposite using L. (Loganiaceae) and antimicrobial activity against multidrug-resistant bacterial strains from diabetic foot ulcer.

Nanobiotechnology has been emerged as an efficient technology for the development of antimicrobial nanoparticles through an eco-friendly approach. In ...

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database.

Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image h...

A Fully Automated Conversational Artificial Intelligence for Weight Loss: Longitudinal Observational Study Among Overweight and Obese Adults.

BACKGROUND: Type 2 diabetes is the most expensive chronic disease in the United States. Two-thirds of US adults have prediabetes or are overweight and...

Development of a Reinforcement Learning-based Evolutionary Fuzzy Rule-Based System for diabetes diagnosis.

The early diagnosis of disease is critical to preventing the occurrence of severe complications. Diabetes is a serious health problem. A variety of me...

Relationship Between Serum Macrophage Migration Inhibitory Factor Level and Insulin Resistance, High-Sensitivity C-Reactive Protein and Visceral Fat Mass in Prediabetes.

BACKGROUND: Growing evidence suggest that macrophage migration inhibitory factor (MIF) plays a vital role in glucose metabolism. We aimed to ascertain...

Comparison of Machine Learning Approaches Toward Assessing the Risk of Developing Cardiovascular Disease as a Long-Term Diabetes Complication.

The estimation of long-term diabetes complications risk is essential in the process of medical decision making. Guidelines for the management of Type ...

An ensemble deep learning based approach for red lesion detection in fundus images.

BACKGROUND AND OBJECTIVES: Diabetic retinopathy (DR) is one of the leading causes of preventable blindness in the world. Its earliest sign are red les...

Hyperinsulinemia and Insulin Receptor Gene Mutation in Nonobese Healthy Subjects in Japan.

CONTEXT: Hyperinsulinemia is often observed in obese people, owing to their insulin resistance accompanied by visceral fat accumulation, but the frequ...

Low-dose Rituximab therapy in resistant idiopathic membranous nephropathy: single-center experience.

BACKGROUND: Persistent significant proteinuria has been associated with increased risk of progression to end-stage kidney disease in patients with idi...

Learning ensemble classifiers for diabetic retinopathy assessment.

Diabetic retinopathy is one of the most common comorbidities of diabetes. Unfortunately, the recommended annual screening of the eye fundus of diabeti...

Phenotype Prediction from Metagenomic Data Using Clustering and Assembly with Multiple Instance Learning (CAMIL).

The recent advent of Metagenome Wide Association Studies (MGWAS) provides insight into the role of microbes on human health and disease. However, the ...

Diabetic retinopathy screening using deep neural network.

IMPORTANCE: There is a burgeoning interest in the use of deep neural network in diabetic retinal screening.

Temporal case-based reasoning for type 1 diabetes mellitus bolus insulin decision support.

Individuals with type 1 diabetes have to monitor their blood glucose levels, determine the quantity of insulin required to achieve optimal glycaemic c...

Real-Time Non-Invasive Detection and Classification of Diabetes Using Modified Convolution Neural Network.

Non-invasive diabetes prediction has been gaining prominence over the last decade. Among many human serums evaluated, human breath emerges as a promis...

Single Nucleotide Polymorphism relevance learning with Random Forests for Type 2 diabetes risk prediction.

OBJECTIVE: The use of artificial intelligence techniques to find out which Single Nucleotide Polymorphisms (SNPs) promote the development of a disease...

Type 2 Diabetes Mellitus Is Associated with Social Recognition Memory Deficit and Altered Dopaminergic Neurotransmission in the Amygdala.

OBJECTIVE: Diabetic neuropathy is a chronic and often disabling condition that affects a significant number of individuals with diabetes mellitus (DM)...

Validation of a Machine Learning Approach for Venous Thromboembolism Risk Prediction in Oncology.

Using kernel machine learning (ML) and random optimization (RO) techniques, we recently developed a set of venous thromboembolism (VTE) risk predictor...