Endocrinology

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

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A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization.

Microscopic examination of pathology slides is essential to disease diagnosis and biomedical researc...

Deep learning for classification of thyroid nodules on ultrasound: validation on an independent dataset.

OBJECTIVES: The purpose is to apply a previously validated deep learning algorithm to a new thyroid ...

Predictors of Remission of Acromegaly following Surgical Treatment in Growth Hormone-Secreting Pituitary Adenoma.

 Surgery is the treatment of choice for growth hormone (GH)-secreting pituitary adenoma. The remiss...

Oncocytic adrenocortical neoplasm of borderline uncertain malignant potential diagnosed after robot-assisted adrenalectomy case report.

BACKGROUND: Adrenal incidentalomas are radiologically discovered tumors that represent a variety of ...

Segmentation of thyroid glands and nodules in ultrasound images using the improved U-Net architecture.

BACKGROUND: Identifying thyroid nodules' boundaries is crucial for making an accurate clinical asses...

Updates of precision medicine in type 2 diabetes.

Diabetes mellitus is prevalent worldwide and affects 1 in 10 adults. Despite the successful developm...

A deep learning nomogram of continuous glucose monitoring data for the risk prediction of diabetic retinopathy in type 2 diabetes.

Continuous glucose monitoring (CGM) data analysis will provide a new perspective to analyze factors ...

Facelift thyroid surgery: a systematic review of indications, surgical and functional outcomes.

OBJECTIVE: To investigate indications, surgical and functional outcomes of robotic or endoscopic fac...

A Novel Deep-Learning-Based CADx Architecture for Classification of Thyroid Nodules Using Ultrasound Images.

Nodules of thyroid cancer occur in the cells of the thyroid as benign or malign types. Thyroid sonog...

Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records.

Background Statins are guideline-recommended medications that reduce cardiovascular events in patien...

Deep Learning-Enabled Morphometric Analysis for Toxicity Screening Using Zebrafish Larvae.

Toxicology studies heavily rely on morphometric analysis to detect abnormalities and diagnose diseas...

Efficacy and Safety of Minimally Invasive Thyroid Surgery: A Network Meta-Analysis.

OBJECTIVES: Minimally invasive and remote surgical approaches for thyroid tumors have been developed...

Deep Learning Prediction of Promoter Mutation Status in Thyroid Cancer Using Histologic Images.

objectives: Telomerase reverse transcriptase () promoter mutation, found in a subset of patients wi...

A Federated Learning-Inspired Evolutionary Algorithm: Application to Glucose Prediction.

In this paper, we propose an innovative Federated Learning-inspired evolutionary framework. Its main...

Prescribing patterns of SGLT-2 inhibitors for patients with heart failure: A two-center analysis.

BACKGROUND: Sodium glucose co-transporter 2 inhibitors (SGLT2i) have been proven to reduce the combi...

Machine learning to improve false-positive results in the Dutch newborn screening for congenital hypothyroidism.

OBJECTIVE: The Dutch Congenital hypothyroidism (CH) Newborn Screening (NBS) algorithm for thyroidal ...

Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques.

The study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and...

GPCRLigNet: rapid screening for GPCR active ligands using machine learning.

Molecules with bioactivity towards G protein-coupled receptors represent a subset of the vast space ...

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