Endocrinology

Deep Learning Algorithm-Based MRI Image in the Diagnosis of Diabetic Macular Edema.

This study investigates the value of magnetic resonance imaging (MRI) based on a deep learning algorithm in the diagnosis of diabetic macular edema (DME) patients. A total of 96 patients with DME were randomly divided into the experimental group (  = 48) and the control group (  = 48). A deep learning 3D convolutional neural network (3D-CNN) algorithm for MRI images of patients with DME was design...

Evaluation of the Antidiabetic Potential of an Isolated Hydroalcoholic Fraction from the Fruit of .

The hydro-alcoholic extract of fruits was investigated for preliminary phytochemical screening and characterized by high-performance thin-layer chromatography. Column chromatography of the hydro-alcoholic extract of eluted with four different combinations of ethyl acetate and methanol yielded four fractions (WCF, WCF, WCF and WCF). One of these fractions, WCF, significantly ( < 0.05) inhibited ...

Postsurgical complications after robot-assisted transaxillary thyroidectomy: critical analysis of a large cohort of European patients.

In the last decade, robot-assisted trans-axillary thyroidectomy has spread rapidly and has been proven to be a safe and effective procedure. However, ...

Objective quantification of nerves in immunohistochemistry specimens of thyroid cancer utilising deep learning.

Accurate quantification of nerves in cancer specimens is important to understand cancer behaviour. Typically, nerves are manually detected and counted...

Predicting age at onset of type 1 diabetes in children using regression, artificial neural network and Random Forest: A case study in Saudi Arabia.

The rising incidence of type 1 diabetes (T1D) among children is an increasing concern globally. A reliable estimate of the age at onset of T1D in chil...

Application of Improved U-Net Convolutional Neural Network for Automatic Quantification of the Foveal Avascular Zone in Diabetic Macular Ischemia.

OBJECTIVES: The foveal avascular zone (FAZ) is a biomarker for quantifying diabetic macular ischemia (DMI), to automate the identification and quantif...

Untangling Computer-Aided Diagnostic System for Screening Diabetic Retinopathy Based on Deep Learning Techniques.

Diabetic Retinopathy (DR) is a predominant cause of visual impairment and loss. Approximately 285 million worldwide population is affected with diabet...

Effectiveness of Artificial Intelligence Models for Cardiovascular Disease Prediction: Network Meta-Analysis.

Heart failure is the most common cause of death in both males and females around the world. Cardiovascular diseases (CVDs), in particular, are the mai...

A Federated Mining Approach on Predicting Diabetes-Related Complications: Demonstration Using Real-World Clinical Data.

Chronic diabetes can lead to microvascular complications, including diabetic eye disease, diabetic kidney disease, and diabetic neuropathy. However, t...

Clinical application of a 5G-based telerobotic ultrasound system for thyroid examination on a rural island: a prospective study.

PURPOSE: To evaluate the feasibility of a 5G-based telerobotic ultrasound (US) system for thyroid examination on a rural island.

Correlation Between Serum AMH Levels and Cardiometabolic Indices in PCOS Women.

INTRODUCTION: Polycystic ovary syndrome (PCOS) has a predilection for several cardio-metabolic disorders in future. Levels of anti-Mullerian hormone (...

Adaptive Control of Nonlinear MIMO System With Orthogonal Endocrine Intelligent Controller.

In this article, a new intelligent hybrid controller is proposed. The controller is based on the combination of the orthogonal endocrine neural networ...

Hybrid deep-learning-based denoising method for compressed sensing in pituitary MRI: comparison with the conventional wavelet-based denoising method.

OBJECTIVES: This study aimed to evaluate the efficacy of a combined wavelet and deep-learning reconstruction (DLR) method for under-sampled pituitary ...

A Novel Extra Tree Ensemble Optimized DL Framework (ETEODL) for Early Detection of Diabetes.

Diabetes has been recognized as a global medical problem for more than half a century. Patients with diabetes can benefit from the Internet of Things ...

A machine learning-based on-demand sweat glucose reporting platform.

Diabetes is a chronic endocrine disease that occurs due to an imbalance in glucose levels and altering carbohydrate metabolism. It is a leading cause ...

Evaluation of Chilled Dog Semen Extended With Sperm Activator.

Within modern biotechnology, different tools and methodologies have been developed to maximize canine semen conservation protocol to optimize reproduc...

Diabetes mellitus risk prediction in the presence of class imbalance using flexible machine learning methods.

BACKGROUND: Early detection and prediction of type two diabetes mellitus incidence by baseline measurements could reduce associated complications in t...

Machine learning-aided risk prediction for metabolic syndrome based on 3 years study.

Metabolic syndrome (MetS) is a group of physiological states of metabolic disorders, which may increase the risk of diabetes, cardiovascular and other...

Thyroid endocrine disruption and hepatotoxicity induced by bisphenol AF: Integrated zebrafish embryotoxicity test and deep learning.

Bisphenol AF (BPAF) is an emerging contaminant prevalent in the environment as one of main substitutes of bisphenol A (BPA). It was found that BPAF ex...

The Comparison of Fixed and Flexible Progestin Primed Ovarian Stimulation on Mature Oocyte Yield in Women at Risk of Premature Ovarian Insufficiency.

While gonadotrophin releasing hormone (GnRH) antagonists have been the standard of pituitary suppression during ovarian stimulation for ART, progestin...