Endocrinology

Data Homogeneity Effect in Deep Learning-Based Prediction of Type 1 Diabetic Retinopathy.

This study is aimed at evaluating a deep transfer learning-based model for identifying diabetic retinopathy (DR) that was trained using a dataset with high variability and predominant type 2 diabetes (T2D) and comparing model performance with that in patients with type 1 diabetes (T1D). The Kaggle dataset, which is a publicly available dataset, was divided into training and testing Kaggle datasets...

Risk Assessment and Determination of Factors That Cause the Development of Hyperinsulinemia in School-Age Adolescents.

: Hyperinsulinemia and insulin resistance are not synonymous; if the risk of developing insulin resistance in adolescents is monitored, they do not necessarily have hyperinsulinemia. It is considered a condition of pre-diabetes and represents a condition of increased risk of developing DM (diabetes mellitus); it can exist for many years without people having the appropriate symptoms. This study ai...

Multi-step ahead predictive model for blood glucose concentrations of type-1 diabetic patients.

Continuous monitoring of blood glucose (BG) levels is a key aspect of diabetes management. Patients with Type-1 diabetes (T1D) require an effective to...

Machine Learning Methods of Regression for Plasmonic Nanoantenna Glucose Sensing.

The measurement and quantification of glucose concentrations is a field of major interest, whether motivated by potential clinical applications or as ...

Evidenced-Based Approaches to Support the Development of Endocrine-Mediated Adverse Outcome Pathways: Challenges and Opportunities.

Detection of maternal and fetal stress from the electrocardiogram with self-supervised representation learning.

In the pregnant mother and her fetus, chronic prenatal stress results in entrainment of the fetal heartbeat by the maternal heartbeat, quantified by t...

The COVID-19 epidemic analysis and diagnosis using deep learning: A systematic literature review and future directions.

Since December 2019, the COVID-19 outbreak has resulted in countless deaths and has harmed all facets of human existence. COVID-19 has been designated...

Alterations of Serum Leptin Levels in Patients with Autoimmune Thyroid Disorders.

Thyroid dysfunction is accompanied with significant metabolic alterations that affect body weight, appetite, and energy expenditure, as well as lipid...

Elevated Levels of Urinary Biomarkers TIMP-2 and IGFBP-7 Predict Acute Kidney Injury in Neonates after Congenital Heart Surgery.

 This article investigated the utility of urine biomarkers tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor binding pr...

Adrenal Insufficiency: Investigating Prevalence and Healthcare Utilization Using Administrative Data.

CONTEXT: Adrenal insufficiency (AI) is an uncommon, life-threatening disorder requiring lifelong treatment with steroid therapy and special attention ...

A stratified analysis of a deep learning algorithm in the diagnosis of diabetic retinopathy in a real-world study.

BACKGROUND: The aim of our research was to prospectively explore the clinical value of a deep learning algorithm (DLA) to detect referable diabetic re...

A Comparative Performance Assessment of Optimized Multilevel Ensemble Learning Model with Existing Classifier Models.

To predict the class level of any classification problem, predictive models are used and mostly a single predictive model is built to predict the clas...

An early model to predict the risk of gestational diabetes mellitus in the absence of blood examination indexes: application in primary health care centres.

BACKGROUND: Gestational diabetes mellitus (GDM) is one of the critical causes of adverse perinatal outcomes. A reliable estimate of GDM in early pregn...

Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions.

Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase ...

Systems biology and machine learning approaches identify drug targets in diabetic nephropathy.

Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the ...

A weakly supervised model for the automated detection of adverse events using clinical notes.

With clinical trials unable to detect all potential adverse reactions to drugs and medical devices prior to their release into the market, accurate po...

Effects of black cumin seed oil on oxidative stress and expression of membrane-cytoskeleton linker proteins, radixin, and moesin in streptozotocin-induced diabetic rat liver.

BACKGROUND AND AIM: This study examined the effects of black cumin seed oil treatment on oxidative stress and the expression of radixin and moesin in ...

Prediction of PCOS and Mental Health Using Fuzzy Inference and SVM.

Polycystic ovarian syndrome (PCOS) is a hormonal disorder found in women of reproductive age. There are different methods used for the detection of PC...

Deep learning-based ultrasonic dynamic video detection and segmentation of thyroid gland and its surrounding cervical soft tissues.

BACKGROUND: The prevalence of thyroid diseases has been increasing year by year. In this study, we established and validated a deep learning method (C...

Desmopressin Stimulation Test in a Pregnant Patient with Cushing's Disease.

OBJECTIVE: Hypothalamic-pituitary-adrenal axis stimulation during pregnancy complicates the investigation of Cushing's syndrome (CS). Our objective wa...