Endocrinology

Prediction of gestational diabetes mellitus at the first trimester: machine-learning algorithms.

PURPOSE: Short- and long-term complications of gestational diabetes mellitus (GDM) involving pregnancies and offspring warrant the development of an effective individualized risk prediction model to reduce and prevent GDM together with its associated co-morbidities. The aim is to use machine learning (ML) algorithms to study data gathered throughout the first trimester in order to predict GDM.

The Impact of Chronic Phthalate Exposure on Rodent Anxiety and Cognition.

BACKGROUND: There is a growing importance for environmental contributions to psychiatric disorders and understanding the impact of the exposome (i.e., pollutants and toxins). For example, increased biomonitoring and epidemiological studies suggest that daily phthalate chemical exposure contributes to neurological and behavioral abnormalities; however, these mechanisms remain poorly understood. The...

High-precision prediction of blood glucose concentration utilizing Fourier transform Raman spectroscopy and an ensemble machine learning algorithm.

Raman spectroscopy has gained popularity in analyzing blood glucose levels due to its non-invasive identification and minimal interference from water....

Attention-based deep learning framework to recognize diabetes disease from cellular retinal images.

A medical disorder known as diabetic retinopathy (DR) affects people who suffer from diabetes. Many people are visually impaired due to DR. Primary ca...

Recent advances in wearable sensors and data analytics for continuous monitoring and analysis of biomarkers and symptoms related to COVID-19.

The COVID-19 pandemic has changed the lives of many people around the world. Based on the available data and published reports, most people diagnosed ...

Explainable artificial intelligence on life satisfaction, diabetes mellitus and its comorbid condition.

This study uses artificial intelligence for testing (1) whether the comorbidity of diabetes and its comorbid condition is very strong in the middle-ag...

URNet: System for recommending referrals for community screening of diabetic retinopathy based on deep learning.

Diabetic retinopathy (DR) will cause blindness if the detection and treatment are not carried out in the early stages. To create an effective treatmen...

Exploring the potential of FDA approved anti-diabetic drugs for repurposing against COVID-19: a core combination of multiple computational strategies and integrated artificial intelligence.

The latest variant of coronavirus is omicron. The World Health Organization (WHO) designated variation 'B.1.1.529' named omicron as a variant of conce...

Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis.

Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to val...

Modeling and insights into the structural characteristics of endocrine-disrupting chemicals.

Endocrine-disrupting chemicals (EDCs) can cause serious harm to human health and the environment; therefore, it is important to rapidly and correctly ...

Editorial: Insights in systems endocrinology: 2021.

A novel approach to quantify calcifications of thyroid nodules in US images based on deep learning: predicting the risk of cervical lymph node metastasis in papillary thyroid cancer patients.

OBJECTIVE: Based on ultrasound (US) images, this study aimed to detect and quantify calcifications of thyroid nodules, which are regarded as one of th...

Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs.

Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulat...

Glucose-6-phosphate dehydrogenase deficiency with coinherited Gaucher disease: A rare association.

Anemia coexisting with Gaucher disease (GD) is often associated with non-hemolytic processes. Few cases of GD with autoimmune hemolytic anemia have be...

Detrimental Effects of Saccharum officinarum Juice on Reproductive Functions of Female Wistar Rats.

Changing dietary compositions have contributed to the growing epidemic of metabolic diseases with serious impacts on several aspects of health, includ...

Interfacing Biology and Electronics with Memristive Materials.

Memristive technologies promise to have a large impact on modern electronics, particularly in the areas of reconfigurable computing and artificial int...

A Deep Learning Regression Model for Photonic Crystal Fiber Sensor With XAI Feature Selection and Analysis.

A Deep Learning Multi-output regression model is employed to correctly model the relationships between optical design parameters of an asymmetric Twin...

Deep learning approach for differentiating indeterminate adrenal masses using CT imaging.

PURPOSE: Distinguishing stage 1-2 adrenocortical carcinoma (ACC) and large, lipid poor adrenal adenoma (LPAA) via imaging is challenging due to overla...

Risk predictions of hospital-acquired pressure injury in the intensive care unit based on a machine learning algorithm.

Pressure injury (PI), or local damage to soft tissues and skin caused by prolonged pressure, remains controversial in the medical world. Patients in i...

Development of in silico classification models for binding affinity to the glucocorticoid receptor.

The endocrine disrupting properties of chemicals acting through the glucocorticoid receptor (GR) have attracted considerable interest. Since there are...