Endocrinology

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

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Showing 1702-1722 of 5,036 articles
Polycystic ovary syndrome: clinical and laboratory variables related to new phenotypes using machine-learning models.

PURPOSE: Polycystic Ovary Syndrome (PCOS) is the most frequent endocrinopathy in women of reproducti...

Weakly supervised learning on unannotated H&E-stained slides predicts BRAF mutation in thyroid cancer with high accuracy.

Deep neural networks (DNNs) that predict mutational status from H&E slides of cancers can enable ine...

Blood glucose concentration prediction based on VMD-KELM-AdaBoost.

The time series of blood glucose concentration in diabetic patients are time-varying, nonlinear, and...

Automated Grading of Diabetic Retinopathy with Ultra-Widefield Fluorescein Angiography and Deep Learning.

PURPOSE: The objective of this study was to establish diagnostic technology to automatically grade t...

A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims.

People with diabetes require lifelong access to healthcare services to delay the onset of complicati...

EAD-Net: A Novel Lesion Segmentation Method in Diabetic Retinopathy Using Neural Networks.

Diabetic retinopathy (DR) is a common chronic fundus disease, which has four different kinds of micr...

The effect of consuming different proportions of hummer fish on biochemical and histopathological changes of hyperglycemic rats.

Hammour fish (grouper fish) are known to be of great nutritional value for human consumption, as the...

Risk prediction of diabetic nephropathy using machine learning techniques: A pilot study with secondary data.

AIMS: This research work presented a comparative study of machine learning (ML), including two objec...

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis.

The fracture risk of patients with diabetes is higher than those of patients without diabetes due to...

Staged reflexive artificial intelligence driven testing algorithms for early diagnosis of pituitary disorders.

BACKGROUND: Sellar masses (SM) frequently present with insidious hormonal dysfunction. We previously...

Hyperthyroidism treatment by alternative therapies based on cupping and dietary-herbal supplementation: a case report.

OBJECTIVES: Hyperthyroidism is characterized by increasing production of thyroid hormone (TH) and de...

MR-Based Radiomics for Differential Diagnosis between Cystic Pituitary Adenoma and Rathke Cleft Cyst.

BACKGROUND: It is often tricky to differentiate cystic pituitary adenoma from Rathke cleft cyst with...

Diagnostic performance of deep-learning-based screening methods for diabetic retinopathy in primary care-A meta-analysis.

BACKGROUND: Diabetic retinopathy (DR) affects 10-24% of patients with diabetes mellitus type 1 or 2 ...

Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model.

Diabetic retinopathy (DR) is an eye disease that alters the blood vessels of a person suffering from...

Application of Pet-CT Fusion Deep Learning Imaging in Precise Radiotherapy of Thyroid Cancer.

This article explores the value of wall F-FDG PET/Cr imaging in the diagnosis of thyroid cancer, stu...

Development and validation of a new diabetes index for the risk classification of present and new-onset diabetes: multicohort study.

In this study, we aimed to propose a novel diabetes index for the risk classification based on machi...

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