Endocrinology

Predicting the evolution of number of native contacts of a small protein by using deep learning approach.

Native contacts (NCs) are one of the most vital parameters in order to define the resemblance of a protein conformation with its native state. Prediction of number of native contacts in a protein is useful in protein folding mechanism. In this work, we focused to predict the time series of the number of NCs of a small protein, insulin monomer by using three neural network based models, namely; Mul...

Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek cohort of 542 individuals with rheumatoid arthritis, or diabetes mellitus, and/or arterial hypertension, using conventional or office-based, laboratory-based blood biomarkers and carotid/femoral ultrasound image-based phen...

A Novel Diabetes Healthcare Disease Prediction Framework Using Machine Learning Techniques.

Diabetes is a chronic disease that continues to be a significant and global concern since it affects the entire population's health. It is a metabolic...

Prediction of Lung Infection during Palliative Chemotherapy of Lung Cancer Based on Artificial Neural Network.

Lung infection seriously affects the effect of chemotherapy in patients with lung cancer and increases pain. The study is aimed at establishing the pr...

A Deep Learning Framework for Automatic Meal Detection and Estimation in Artificial Pancreas Systems.

Current artificial pancreas (AP) systems are hybrid closed-loop systems that require manual meal announcements to manage postprandial glucose control ...

Artificial intelligence approaches to the determinants of women's vaginal dryness using general hospital data.

The aim of this study is to analyse the determinants of women's vaginal dryness using machine learning. Data came from Korea University Anam Hospital ...

Robotic Adrenalectomy Using the da Vinci SP Robotic System: Technical Feasibility Comparison with Single-Port Access Using the da Vinci Multi-arm Robotic System.

BACKGROUND: Laparoscopic adrenalectomy is the gold standard for adrenal tumor; however, robotic adrenal surgery has gained interest recently. For mini...

Panoramic tongue imaging and deep convolutional machine learning model for diabetes diagnosis in humans.

Diabetes is a serious metabolic disorder with high rate of prevalence worldwide; the disease has the characteristics of improper secretion of insulin ...

Ambiguous and Incomplete: Natural Language Processing Reveals Problematic Reporting Styles in Thyroid Ultrasound Reports.

OBJECTIVE: Natural language processing (NLP) systems convert unstructured text into analyzable data. Here, we describe the performance measures of NLP...

Thin-Slice Pituitary MRI with Deep Learning-Based Reconstruction for Preoperative Prediction of Cavernous Sinus Invasion by Pituitary Adenoma: A Prospective Study.

BACKGROUND AND PURPOSE: Accurate radiologic prediction of cavernous sinus invasion by pituitary adenoma remains challenging. We aimed to assess whethe...

Preoperative oral carbohydrate loading: Effects on intraoperative blood glucose levels, post-operative nausea and vomiting, and intensive care unit stay.

BACKGROUND AND AIMS: Preoperative fasting imparts safety to patients from aspiration of gastric contents, but undue fasting may predispose to hypoglyc...

Deep Learning to Detect OCT-derived Diabetic Macular Edema from Color Retinal Photographs: A Multicenter Validation Study.

PURPOSE: To validate the generalizability of a deep learning system (DLS) that detects diabetic macular edema (DME) from 2-dimensional color fundus ph...

Deep learning-based pancreas volume assessment in individuals with type 1 diabetes.

Pancreas volume is reduced in individuals with diabetes and in autoantibody positive individuals at high risk for developing type 1 diabetes (T1D). St...

Assessment of the effect of sub-lethal acute toxicity of Emamectin benzoate in using multiple biomarker approach.

Emamectin benzoate (EMB) is a potent neurotoxin agent, widely used for ectoparasites control in aquaculture, but their detailed toxicological implicat...

Brain Tumor/Mass Classification Framework Using Magnetic-Resonance-Imaging-Based Isolated and Developed Transfer Deep-Learning Model.

With the advancement in technology, machine learning can be applied to diagnose the mass/tumor in the brain using magnetic resonance imaging (MRI). Th...

Acute Effects of Nicotine on Physiological Responses and Sport Performance in Healthy Baseball Players.

There is interest in whether nicotine could enhance attention in sporting performance, but evidence on the acute effect of nicotine on physical respon...

Rhabdomyolysis: An evidence-based approach.

A 76-year-old lady was found on the floor following a fall at home. She was uninjured, but unable to get up, and had been lying on the floor for rough...

Attenuation of Oxidative Stress, Interleukin-6, High-Sensitivity C-Reactive Protein, Plasminogen Activator Inhibitor-1, and Fibrinogen with Oral Vitamin D Supplementation in Patients with T2DM having Vitamin D Deficiency.

 Type 2 diabetes mellitus (T2DM) associated with oxidative stress and inflammation causes endothelial dysfunction, which promotes cardiovascular risk...

Is Vitamin D Deficiency Associated with Chronic Lymphocytic Thyroiditis?

OBJECTIVES: Vitamin D deficiency is a very common global health problem. Evidence from recent studies focuses on the extraskeletal effects of vitamin ...

Explainable Machine Learning for Atrial Fibrillation in the General Population Using a Generalized Additive Model　- A Cross-Sectional Study.

Atrial fibrillation (AF) is the most common arrhythmia and is associated with increased thromboembolic stroke risk and heart failure. Although variou...