Endocrinology

Diabetes

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

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Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks.

Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial...

Artificial intelligence assists identification and pathologic classification of glomerular lesions in patients with diabetic nephropathy.

BACKGROUND: Glomerular lesions are the main injuries of diabetic nephropathy (DN) and are used as a ...

The role of machine learning in advancing diabetic foot: a review.

BACKGROUND: Diabetic foot complications impose a significant strain on healthcare systems worldwide,...

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets.

Type 1 diabetes (T1D) is a chronic condition in which beta cells are destroyed by immune cells. Desp...

Diabetic retinopathy prediction based on vision transformer and modified capsule network.

Diabetic retinopathy is considered one of the most common diseases that can lead to blindness in the...

Autonomous artificial intelligence versus teleophthalmology for diabetic retinopathy.

To assess the role of artificial intelligence (AI) based automated software for detection of Diabet...

Progression from Prediabetes to Diabetes in a Diverse U.S. Population: A Machine Learning Model.

To date, there are no widely implemented machine learning (ML) models that predict progression from...

Predicting FFAR4 agonists using structure-based machine learning approach based on molecular fingerprints.

Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intr...

Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G.

Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that...

A new intelligent system based deep learning to detect DME and AMD in OCT images.

Optical Coherence Tomography (OCT) is widely recognized as the leading modality for assessing ocular...

Effects of tacrolimus on proteinuria in Chinese and Indian patients with idiopathic membranous nephropathy: the results of machine learning study.

PURPOSE: The present study aims to explore the effects of tacrolimus on proteinuria in patients with...

Multimodality Fusion Strategies in Eye Disease Diagnosis.

Multimodality fusion has gained significance in medical applications, particularly in diagnosing cha...

UroAngel: a single-kidney function prediction system based on computed tomography urography using deep learning.

BACKGROUND: Accurate estimation of the glomerular filtration rate (GFR) is clinically crucial for de...

Artificial intelligence-enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes.

AIM: To develop and employ machine learning (ML) algorithms to analyse electrocardiograms (ECGs) for...

OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods.

Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical appli...

Physical Activity Detection for Diabetes Mellitus Patients Using Recurrent Neural Networks.

Diabetes mellitus (DM) is a persistent metabolic disorder associated with the hormone insulin. The t...

Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence.

The rapid surge in artificial intelligence (AI) has dominated technological innovation in today's so...

Response accuracy of ChatGPT 3.5 Copilot and Gemini in interpreting biochemical laboratory data a pilot study.

With the release of ChatGPT at the end of 2022, a new era of thinking and technology use has begun. ...

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