Diabetes

Effect of Korth. Leaves on Superoxide Dismutase, HbA1c Levels and Insulin Expression in Hyperglycemic Rats.

AIM: This study aimed to investigate Korth. leaves. the activity of ethanol extract in hypoglycemic, superoxide dismutase (SOD), glycosylated haemoglobin (HbA1c) and detection of insulin expression by immunochemistry.

An artificial intelligence-based deep learning algorithm for the diagnosis of diabetic neuropathy using corneal confocal microscopy: a development and validation study.

AIMS/HYPOTHESIS: Corneal confocal microscopy is a rapid non-invasive ophthalmic imaging technique that identifies peripheral and central neurodegenerative disease. Quantification of corneal sub-basal nerve plexus morphology, however, requires either time-consuming manual annotation or a less-sensitive automated image analysis approach. We aimed to develop and validate an artificial intelligence-ba...

Application of machine learning methodology to assess the performance of DIABETIMSS program for patients with type 2 diabetes in family medicine clinics in Mexico.

BACKGROUND: The study aimed to assess the performance of a multidisciplinary-team diabetes care program called DIABETIMSS on glycemic control of type ...

A machine-learning approach to predict postprandial hypoglycemia.

BACKGROUND: For an effective artificial pancreas (AP) system and an improved therapeutic intervention with continuous glucose monitoring (CGM), predic...

A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.

BACKGROUND: Diabetes and cardiovascular disease are two of the main causes of death in the United States. Identifying and predicting these diseases in...

Validation of a Deep Learning Algorithm for Diabetic Retinopathy.

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Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a major public health burden. Self-management of diabetes including maintaining a healthy lifestyle is ...

Synthesis, Type II diabetes inhibitory activity, antimicrobial evaluation and docking studies of indeno[1,2-]pyrazol-4(1)-ones.

We report a convenient and efficient synthesis of indeno[1,2-]pyrazol-4(1)-ones () by the reaction of a variety of 2-acyl-(1)-indene-1,3(2)-diones () ...

Predicting diabetes second-line therapy initiation in the Australian population via time span-guided neural attention network.

INTRODUCTION: The first line of treatment for people with Diabetes mellitus is metformin. However, over the course of the disease metformin may fail t...

Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival.

Background Small molecule kinase inhibitors (KIs) are a class of agents currently used for treatment of various cancers. Unfortunately, treatment of c...

Utility of Big Data in Predicting Short-Term Blood Glucose Levels in Type 1 Diabetes Mellitus Through Machine Learning Techniques.

Machine learning techniques combined with wearable electronics can deliver accurate short-term blood glucose level prediction models. These models can...

Predictive models for diabetes mellitus using machine learning techniques.

BACKGROUND: Diabetes Mellitus is an increasingly prevalent chronic disease characterized by the body's inability to metabolize glucose. The objective ...

Sepsis in Latent Autoimmune Diabetes in Adults with Diabetic Ketoacidosis: A Case Report.

BACKGROUND: This case report intends to highlight the challenge in diagnosing type 1 diabetes on an adult patient. Latent Autoimmune Diabetes in Adult...

Comparing information extraction techniques for low-prevalence concepts: The case of insulin rejection by patients.

OBJECTIVE: To comparatively evaluate a range of Natural Language Processing (NLP) approaches for Information Extraction (IE) of low-prevalence concept...

IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge.

Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss, predominantly affecting the working-age population across the globe. Scre...

One-shot optimization of multiple enzyme parameters: Tailoring glucose oxidase for pH and electron mediators.

Enzymes are biological catalysts with many industrial applications, but natural enzymes are usually unsuitable for industrial processes because they a...

Predicting short- and long-term glycated haemoglobin response after insulin initiation in patients with type 2 diabetes mellitus using machine-learning algorithms.

AIM: To assess the potential of supervised machine-learning techniques to identify clinical variables for predicting short-term and long-term glycated...

Automated diagnosis and quantitative analysis of plus disease in retinopathy of prematurity based on deep convolutional neural networks.

BACKGROUND: The purpose of this study was to develop an automated diagnosis and quantitative analysis system for plus disease. The system provides a d...

Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.

PURPOSE: To develop and validate a deep learning (DL) algorithm that predicts referable glaucomatous optic neuropathy (GON) and optic nerve head (ONH)...

Building Risk Prediction Models for Type 2 Diabetes Using Machine Learning Techniques.

INTRODUCTION: As one of the most prevalent chronic diseases in the United States, diabetes, especially type 2 diabetes, affects the health of millions...