Endocrinology

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

4,980 articles
Stay Ahead - Weekly Endocrinology research updates
Subscribe
Browse Specialties
Showing 694-714 of 4,980 articles
Mixed-effects neural network modelling to predict longitudinal trends in fasting plasma glucose.

BACKGROUND: Accurate fasting plasma glucose (FPG) trend prediction is important for management and t...

The Effect of Intravenous Lidocaine on EC50 of Remifentanil for Preventing Cough During Emergence in Female for Thyroid Surgery Anesthesia.

OBJECTIVE: To evaluate the effect of intravenous lidocaine injection on the half-maximum effective c...

Leveraging artificial intelligence and machine learning to accelerate discovery of disease-modifying therapies in type 1 diabetes.

Progress in developing therapies for the maintenance of endogenous insulin secretion in, or the prev...

Patient and practitioner perceptions around use of artificial intelligence within the English NHS diabetic eye screening programme.

AIMS: Automated retinal image analysis using Artificial Intelligence (AI) can detect diabetic retino...

Identification and validation of the diagnostic biomarker MFAP5 for CAVD with type 2 diabetes by bioinformatics analysis.

INTRODUCTION: Calcific aortic valve disease (CAVD) is increasingly prevalent among the aging populat...

Actuation-Mediated Compression of a Mechanoresponsive Hydrogel by Soft Robotics to Control Release of Therapeutic Proteins.

Therapeutic proteins, the fastest growing class of pharmaceuticals, are subject to rapid proteolytic...

A prior-knowledge-guided dynamic attention mechanism to predict nocturnal hypoglycemic events in type 1 diabetes.

Nocturnal hypoglycemia is a critical problem faced by diabetic patients. Failure to intervene in tim...

An explainable analysis of diabetes mellitus using statistical and artificial intelligence techniques.

BACKGROUND: Diabetes mellitus (DM) is a chronic disease prevalent worldwide, requiring a multifacete...

Ensemble deep learning and EfficientNet for accurate diagnosis of diabetic retinopathy.

Diabetic Retinopathy (DR) stands as a significant global cause of vision impairment, underscoring th...

Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases.

Thyroid diseases, including functional and neoplastic diseases, bring a huge burden to people's heal...

Clinical characteristics of adrenal crisis in 371 adult patients with glucocorticoid-induced adrenal insufficiency.

BACKGROUND: Glucocorticoid-induced adrenal insufficiency (GIAI) is a hypothalamic-pituitary-adrenal ...

L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction.

Pre-training strategies based on self-supervised learning (SSL) have demonstrated success as pretext...

Potential shared mechanisms in atopic dermatitis and type 2 diabetes identified via transcriptomic and machine learning approaches.

Although atopic dermatitis (AD) and type 2 diabetes mellitus (T2DM) may appear clinically and pathop...

Endocrine disruptor identification and multitoxicity level assessment of organic chemicals: An example of multiple machine learning models.

Endocrine-disrupting chemicals (EDCs) pollution is a major global environmental issue. Assessing the...

Effects of melatonin on the mitogen-activated protein kinase signaling genes in hypoxic Leydig cells.

Leydig cells play a crucial role in male reproductive physiology, and their dysfunction is often ass...

XGBoost-based nomogram for predicting lymph node metastasis in endometrial carcinoma.

This study aims to construct and optimize risk prediction models for lymph node metastasis (LNM) in ...

Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management.

One of the health challenges in the 21st century is to rethink approaches to non-communicable diseas...

Browse Specialties