Endocrinology

Association between vitamin D deficiency and insulin resistance markers in euthyroid non-diabetic individuals.

AIM: To evaluate the association between vitamin D deficiency and insulin resistance (IR) or hyperin...

Evaluation of Artificial Intelligence-Based Grading of Diabetic Retinopathy in Primary Care.

IMPORTANCE: There has been wide interest in using artificial intelligence (AI)-based grading of reti...

Fibroblast growth factor23 is associated with axonal integrity and neural network architecture in the human frontal lobes.

Elevated levels of FGF23 in individuals with chronic kidney disease (CKD) are associated with advers...

Effect of deglutition aids on the inhibitory effect of orally disintegrating tablets of voglibose on the postprandial elevation of blood glucose levels: a case investigating the interaction between xanthan gum and voglibose.

In this study, we first performed a disintegration test of the voglibose orally disintegrating (V-OD...

Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.

In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care...

Mixed effect machine learning: A framework for predicting longitudinal change in hemoglobin A1c.

Accurate and reliable prediction of clinical progression over time has the potential to improve the ...

Machine learning identifies interacting genetic variants contributing to breast cancer risk: A case study in Finnish cases and controls.

We propose an effective machine learning approach to identify group of interacting single nucleotide...

Remote-access thyroid surgery-progress, assessment, and reflection.

The usefulness of fine-needle aspirates for detection of recurrent carcinoma in the thyroid bed.

INTRODUCTION: Locoregional recurrence of thyroid carcinoma has a negative impact on patient prognosi...

Identifying people at risk of developing type 2 diabetes: A comparison of predictive analytics techniques and predictor variables.

BACKGROUND: The present study aims to identify the patients at risk of type 2 diabetes (T2D). There ...

Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction.

Many chemicals that disrupt endocrine function have been linked to a variety of adverse biological o...

Computational characterization and identification of human polycystic ovary syndrome genes.

Human polycystic ovary syndrome (PCOS) is a highly heritable disease regulated by genetic and enviro...

Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices.

Artificial Intelligence (AI) has long promised to increase healthcare affordability, quality and acc...

Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms.

Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF dura...

Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.

BACKGROUND: Oncotype Dx is a validated genetic analysis that provides a recurrence score (RS) to qua...

Low Protein Z Level: A Thrombophilic Risk Biomarker for Acute Coronary Syndrome.

Acute coronary syndrome (ACS) encompasses a range of thrombotic coronary artery diseases. Protein Z ...

Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms.

BACKGROUND: The risk factors of diabetic retinopathy (DR) were investigated extensively in the past ...

Using Machine Learning to Aid the Interpretation of Urine Steroid Profiles.

BACKGROUND: Urine steroid profiles are used in clinical practice for the diagnosis and monitoring of...

Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrie...

Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability.

OBJECTIVE: Radiographic bone age assessment (BAA) is used in the evaluation of pediatric endocrine a...

Neural network-based model predictive control for type 1 diabetic rats on artificial pancreas system.

Artificial pancreas system (APS) is a viable option to treat diabetic patients. Researchers, however...