Endocrinology

Latest AI and machine learning research in endocrinology for healthcare professionals.

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Hybrid deep-learning-based denoising method for compressed sensing in pituitary MRI: comparison with the conventional wavelet-based denoising method.

OBJECTIVES: This study aimed to evaluate the efficacy of a combined wavelet and deep-learning recons...

A Novel Extra Tree Ensemble Optimized DL Framework (ETEODL) for Early Detection of Diabetes.

Diabetes has been recognized as a global medical problem for more than half a century. Patients with...

A machine learning-based on-demand sweat glucose reporting platform.

Diabetes is a chronic endocrine disease that occurs due to an imbalance in glucose levels and alteri...

Evaluation of Chilled Dog Semen Extended With Sperm Activator.

Within modern biotechnology, different tools and methodologies have been developed to maximize canin...

Machine learning-aided risk prediction for metabolic syndrome based on 3 years study.

Metabolic syndrome (MetS) is a group of physiological states of metabolic disorders, which may incre...

Diabetes mellitus risk prediction in the presence of class imbalance using flexible machine learning methods.

BACKGROUND: Early detection and prediction of type two diabetes mellitus incidence by baseline measu...

Thyroid endocrine disruption and hepatotoxicity induced by bisphenol AF: Integrated zebrafish embryotoxicity test and deep learning.

Bisphenol AF (BPAF) is an emerging contaminant prevalent in the environment as one of main substitut...

The Comparison of Fixed and Flexible Progestin Primed Ovarian Stimulation on Mature Oocyte Yield in Women at Risk of Premature Ovarian Insufficiency.

While gonadotrophin releasing hormone (GnRH) antagonists have been the standard of pituitary suppres...

Non-invasively accuracy enhanced blood glucose sensor using shallow dense neural networks with NIR monitoring and medical features.

Non-invasive and accurate method for continuous blood glucose monitoring, the self-testing of blood ...

Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual Screening by Using a New Deep-Learning Classifier.

CYP3A4 is the main human enzyme responsible for phase I metabolism of dietary compounds, prescribed ...

The adoption of deep learning interpretability techniques on diabetic retinopathy analysis: a review.

Diabetic retinopathy (DR) is a chronic eye condition that is rapidly growing due to the prevalence o...

Deep Learning Algorithm for Automated Detection of Polycystic Ovary Syndrome Using Scleral Images.

The high prevalence of polycystic ovary syndrome (PCOS) among reproductive-aged women has attracted ...

Candidate Circulating Biomarkers of Spontaneous Miscarriage After IVF-ET Identified via Coupling Machine Learning and Serum Lipidomics Profiling.

Spontaneous miscarriage is a common pregnancy complication. Multiple etiologies have been proposed s...

External validation of deep learning-based bone-age software: a preliminary study with real world data.

Artificial intelligence (AI) is increasingly being used in bone-age (BA) assessment due to its compl...

End-to-end diabetic retinopathy grading based on fundus fluorescein angiography images using deep learning.

PURPOSE: To develop and validate a deep learning system for diabetic retinopathy (DR) grading based ...

A multi-task two-path deep learning system for predicting the invasiveness of craniopharyngioma.

BACKGROUND AND OBJECTIVE: Craniopharyngioma is a kind of benign brain tumor in histography. However,...

Necessity of Local Modification for Deep Learning Algorithms to Predict Diabetic Retinopathy.

Deep learning (DL) algorithms are used to diagnose diabetic retinopathy (DR). However, most of these...

An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus.

Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal a...

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