Endocrinology

Diabetes

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

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Showing 1387-1407 of 2,607 articles
Type IV Collagen 7S Is the Most Accurate Test For Identifying Advanced Fibrosis in NAFLD With Type 2 Diabetes.

This study aimed to examine whether the diagnostic accuracy of four noninvasive tests (NITs) for det...

Developing an Individual Glucose Prediction Model Using Recurrent Neural Network.

In this study, we propose a personalized glucose prediction model using deep learning for hospitaliz...

The use of geroprotectors to prevent multimorbidity: Opportunities and challenges.

Over 60 % of people over the age of 65 will suffer from multiple diseases concomitantly but the comm...

Screening for Diabetic Retinopathy Using an Automated Diagnostic System Based on Deep Learning: Diagnostic Accuracy Assessment.

PURPOSE: To evaluate the diagnostic accuracy of a diagnostic system software for the automated scree...

Evaluation of a Deep Learning-Derived Quantitative Retinopathy of Prematurity Severity Scale.

PURPOSE: To evaluate the clinical usefulness of a quantitative deep learning-derived vascular severi...

Predicting Diabetic Neuropathy Risk Level Using Artificial Neural Network and Clinical Parameters of Subjects With Diabetes.

BACKGROUND: A risk assessment tool has been developed for automated estimation of level of neuropath...

Mesenchymal stem cell conditioned medium ameliorates diabetic serum-induced insulin resistance in 3T3-L1 cells.

BACKGROUND: Pharmacological factors used to induce insulin resistance (IR) in models may not mimic ...

TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings.

BACKGROUND: Cytokines are a class of small proteins that act as chemical messengers and play a signi...

[Leptin sexual dimorphism, insulin resistance, and body composition in normal weight prepubescent].

INTRODUCTION: The prepubertal stage is a critical period of body fat development, in which leptin an...

Replacing the internal standard to estimate micropollutants using deep and machine learning.

Similar to the worldwide proliferation of urbanization, micropollutants have been involved in aquati...

Defining and Classifying New Subgroups of Diabetes.

An etiologically based classification of diabetes is needed to account for the heterogeneity of type...

Multi-Hour Blood Glucose Prediction in Type 1 Diabetes: A Patient-Specific Approach Using Shallow Neural Network Models.

Considering current insulin action profiles and the nature of glycemic responses to insulin, there ...

Facial erythema detects diabetic neuropathy using the fusion of machine learning, random matrix theory and self organized criticality.

Rubeosis faciei diabeticorum, caused by microangiopathy and characterized by a chronic facial erythe...

Automated Segmentation of Retinal Fluid Volumes From Structural and Angiographic Optical Coherence Tomography Using Deep Learning.

PURPOSE: We proposed a deep convolutional neural network (CNN), named Retinal Fluid Segmentation Net...

Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 Diabetes.

Early and precise identification of individuals with prediabetes and type 2 diabetes (T2D) at risk f...

Important Tools for Use by Pediatric Endocrinologists in the Assessment of Short Stature.

Assessment and management of children with growth failure has improved greatly over recent years. Ho...

A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability.

Health data that are publicly available are valuable resources for digital health research. Several ...

Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records.

Type II diabetes mellitus (T2DM) is a significant public health concern with multiple known risk fac...

THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.

AIM: To develop and evaluate an artificial intelligence triage system with high sensitivity for dete...

Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

BACKGROUND: An estimated 425 million people globally have diabetes, accounting for 12% of the world'...

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