Endocrinology

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.

Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifications and drug intervention can prevent diabetes, therefore, an early identification of high risk individuals is important to design targeted prevention strategies. In this paper, we present an automatic tool that uses machine learning techniques to predict the development of type 2 diabetes melli...

An enhanced deep learning approach for brain cancer MRI images classification using residual networks.

Cancer is the second leading cause of death after cardiovascular diseases. Out of all types of cancer, brain cancer has the lowest survival rate. Brain tumors can have different types depending on their shape, texture, and location. Proper diagnosis of the tumor type enables the doctor to make the correct treatment choice and help save the patient's life. There is a high need in the Artificial Int...

Computational modeling of the monoaminergic neurotransmitter and male neuroendocrine systems in an analysis of therapeutic neuroadaptation to chronic antidepressant.

Second-line depression treatment involves augmentation with one (rarely two) additional drugs, of chronic administration of a selective serotonin reup...

Pulse Wave Velocity and Machine Learning to Predict Cardiovascular Outcomes in Prediabetic and Diabetic Populations.

Few studies have addressed the predictive value of arterial stiffness determined by pulse wave velocity (PWV) in a high-risk population with no preval...

Computer-Aided Diagnosis Systems in Diagnosing Malignant Thyroid Nodules on Ultrasonography: A Systematic Review and Meta-Analysis.

BACKGROUND: Computer-aided diagnosis (CAD) systems are being applied to the ultrasonographic diagnosis of malignant thyroid nodules, but it remains co...

Global transcriptome analysis reveals relevant effects at environmental concentrations of cypermethrin in honey bees (Apis mellifera).

Cypermethrin is a frequently used insecticide in agriculture and households but its chronic and molecular effects are poorly known are . Here we descr...

Glycemic-aware metrics and oversampling techniques for predicting blood glucose levels using machine learning.

Techniques using machine learning for short term blood glucose level prediction in patients with Type 1 Diabetes are investigated. This problem is sig...

A New Era for Cyborg Science Is Emerging: The Promise of Cyborganic Beings.

Living flesh, hacked beyond known biological borders, and sophisticated machineries, made by humans, are currently being united to address some of the...

Diagnosis of Thyroid Nodules: Performance of a Deep Learning Convolutional Neural Network Model vs. Radiologists.

Computer-aided diagnosis (CAD) systems hold potential to improve the diagnostic accuracy of thyroid ultrasound (US). We aimed to develop a deep learni...

Biotin supplement interference with immunoassays for parathyroid hormone and 25-hydroxyvitamin D in a patient with metabolic bone disease on maintenance hemodialysis.

Biotin (vitamin B7) is a dietary supplement that can lead to falsely abnormal endocrine function tests. The impact of biotin on both 25-hydroxyvitamin...

Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration.

PURPOSE: To validate the performance of a commercially available, CE-certified deep learning (DL) system, RetCAD v.1.3.0 (Thirona, Nijmegen, The Nethe...

Machine learning-based multiparametric MRI radiomics for predicting the aggressiveness of papillary thyroid carcinoma.

PURPOSE: To investigate the predictive capability of machine learning-based multiparametric magnetic resonance (MR) imaging radiomics for evaluating t...

Identification of repurposable drugs with beneficial effects on glucose control in type 2 diabetes using machine learning.

Despite effective medications, rates of uncontrolled glucose levels in type 2 diabetes remain high. We aimed to test the utility of machine learning a...

Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction.

The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyro...

Powdered coconut water (ACP 406®) as an alternative base culture medium for culture of goat preantral follicles enclosed in ovarian tissue.

This study evaluated a powdered coconut water solution (ACP 406®) as a base culture medium on the survival and development of goat preantral follicl...

Effect of bacterial endotoxin lipopolysaccharide treatment on duck Leydig cells.

This study aimed to investigate the effects of bacterial endotoxin lipopolysaccharide (LPS) on hormone production and gene expression in duck Leydig c...

AOCT-NET: a convolutional network automated classification of multiclass retinal diseases using spectral-domain optical coherence tomography images.

Since introducing optical coherence tomography (OCT) technology for 2D eye imaging, it has become one of the most important and widely used imaging mo...

Effect of Korth. Leaves on Superoxide Dismutase, HbA1c Levels and Insulin Expression in Hyperglycemic Rats.

AIM: This study aimed to investigate Korth. leaves. the activity of ethanol extract in hypoglycemic, superoxide dismutase (SOD), glycosylated haemogl...

An artificial intelligence-based deep learning algorithm for the diagnosis of diabetic neuropathy using corneal confocal microscopy: a development and validation study.

AIMS/HYPOTHESIS: Corneal confocal microscopy is a rapid non-invasive ophthalmic imaging technique that identifies peripheral and central neurodegenera...

Application of machine learning methodology to assess the performance of DIABETIMSS program for patients with type 2 diabetes in family medicine clinics in Mexico.

BACKGROUND: The study aimed to assess the performance of a multidisciplinary-team diabetes care program called DIABETIMSS on glycemic control of type ...