Endocrinology

A new method for automatic counting of ovarian follicles on whole slide histological images based on convolutional neural network.

The ovary is a complex endocrine organ that shows significant structural and functional changes in the female reproductive system over recurrent cycles. There are different types of follicles in the ovarian tissue. The reproductive potential of each individual depends on the numbers of these follicles. However, genetic mutations, toxins, and some specific drugs have an effect on follicles. To dete...

Utilizing hybrid functional fuzzy wavelet neural networks with a teaching learning-based optimization algorithm for medical disease diagnosis.

Accurate medical disease diagnosis is considered to be an important classification problem. The main goal of the classification process is to determine the class to which a certain pattern belongs. In this article, a new classification technique based on a combination of The Teaching Learning-Based Optimization (TLBO) algorithm and Fuzzy Wavelet Neural Network (FWNN) with Functional Link Neural Ne...

Deep learning driven QSAR model for environmental toxicology: Effects of endocrine disrupting chemicals on human health.

Over 80,000 endocrine-disrupting chemicals (EDCs) are considered emerging contaminants (ECs), which are of great concern due to their effects on human...

[Maturity Onset Diabetes of the Young: case report].

BACKGROUND: Maturity Onset Diabetes of the Young (MODY) is a type of diabetes that results from mutations in 13 known genes that play a role in the de...

Brain tumor classification using deep CNN features via transfer learning.

Brain tumor classification is an important problem in computer-aided diagnosis (CAD) for medical applications. This paper focuses on a 3-class classif...

Minimizing postprandial hypoglycemia in Type 1 diabetes patients using multiple insulin injections and capillary blood glucose self-monitoring with machine learning techniques.

BACKGROUND: Diabetic patients treated with intensive insulin therapies require a tight glycemic control and may benefit from advanced tools to predict...

Analysis of the Deleterious Single Nucleotide Polymorphisms Impact on Estrogen Receptor Alpha-p53 Interaction: A Machine Learning Approach.

Breast cancer is a leading cancer type and one of the major health issues faced by women around the world. Some of its major risk factors include body...

Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography.

BACKGROUND AND OBJECTIVES: Spectral Domain Optical Coherence Tomography (SD-OCT) is a volumetric imaging technique that allows measuring patterns betw...

Mitochondrial Psychobiology: Foundations and Applications.

Mitochondrial psychobiology is the study of the interactions between psychological states and the biological processes that take place within mitochon...

Machine-learning to stratify diabetic patients using novel cardiac biomarkers and integrative genomics.

BACKGROUND: Diabetes mellitus is a chronic disease that impacts an increasing percentage of people each year. Among its comorbidities, diabetics are t...

Ontology-based metabolomics data integration with quality control.

 The complications that arise when performing meta-analysis of datasets from multiple metabolomics studies are addressed with computational methods th...

Reproduction study using public data of: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs.

We have attempted to reproduce the results in Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal...

HTR2C Gene Variant and Salivary Cortisol Levels after Endurance Physical Activity: A Pilot Study.

INTRODUCTION: The 5-hydroxytryptamine 2C receptor (HTR2C) rs6318 polymorphism has been associated with increased sensitivity to stress. This study inv...

SOCIETY FOR ENDOCRINOLOGY EMERGENCY ENDOCRINE GUIDANCE: Emergency management of acute hypocalcaemia in adult patients.

In this addendum to the above paper, the Society for Endocrinology Clinical Committee and the original authors provide additional advice on the dose e...

Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.

Applying data mining and machine learning (ML) techniques to clinical data might identify predictive biomarkers for diabetic nephropathy (DN), a commo...

Promising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology.

The lifestyle of modern society has changed significantly with the emergence of artificial intelligence (AI), machine learning (ML), and deep learning...

Assessment of risk based on variant pathways and establishment of an artificial neural network model of thyroid cancer.

BACKGROUND: This study aimed to establish an artificial neural network (ANN) model based on variant pathways to predict the risk of thyroid cancer.

Surgical Approaches to the Adrenal Gland.

Adrenalectomy can be performed open, endoscopically or robotically, utilizing a transabdominal or retroperitoneal approach. This chapter describes the...

Lessons from Two Design-Build-Test-Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning.

The Design-Build-Test-Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabol...

Instant White Rice with Pigmented Giant Embryonic Rice Improves Glucose Metabolism and Inhibits Oxidative Stress in High-Fat Diet-Fed Mice.

The effects of instant cooked rice made from a combination of white rice and pigmented giant embryonic Keunnunjami rice, in comparison with those of i...