Endocrinology

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

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Showing 2185-2205 of 5,041 articles
Application of Machine Learning to Identify Clustering of Cardiometabolic Risk Factors in U.S. Adults.

The aim of this study is to compare some machine learning methods with traditional statistical para...

On building a diabetes centric knowledge base via mining the web.

BACKGROUND: Diabetes has become one of the hot topics in life science researches. To support the ana...

Convolutional Recurrent Neural Networks for Glucose Prediction.

Control of blood glucose is essential for diabetes management. Current digital therapeutic approache...

A data-driven approach to referable diabetic retinopathy detection.

UNLABELLED: Prior art on automated screening of diabetic retinopathy and direct referral decision sh...

Evolution Strategies in Transaxillary Robotic Thyroidectomy: Considerations on the First 449 Cases Performed.

BACKGROUND: In the past 20 years, the fast spread of new surgical technologies has reached an import...

A multi-scale data fusion framework for bone age assessment with convolutional neural networks.

Bone age assessment (BAA) has various clinical applications such as diagnosis of endocrine disorders...

Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT.

PURPOSE: To develop a deep learning-based computer-aided diagnosis (CAD) system for use in the CT di...

[Robot-assisted transaxillary thyroid surgery; 5 years later].

Five years ago, robot-assisted transaxillary thyroidectomy (RATT) was introduced in the Netherlands....

Risk-based postprandial hypoglycemia forecasting using supervised learning.

BACKGROUND: Predicting insulin-induced postprandial hypoglycemic events is critical for the safety o...

Detecting Hypoglycemia Incidents Reported in Patients' Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance.

BACKGROUND: Improper dosing of medications such as insulin can cause hypoglycemic episodes, which ma...

Light-driven ultrasensitive self-powered cytosensing of circulating tumor cells via integration of biofuel cells and a photoelectrochemical strategy.

Herein, a light-driven, membrane-less and mediator-less self-powered cytosensing platform via integr...

Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data.

It is very significant to explore the intrinsic differences in breast cancer subtypes. These intrins...

Feasibility of simple machine learning approaches to support detection of non-glaucomatous visual fields in future automated glaucoma clinics.

OBJECTIVES: To assess the performance of feed-forward back-propagation artificial neural networks (A...

Detecting abnormal thyroid cartilages on CT using deep learning.

PURPOSE: The purpose of this study was to evaluate the performance of a deep learning algorithm in d...

Accuracy of ultrawide-field fundus ophthalmoscopy-assisted deep learning for detecting treatment-naïve proliferative diabetic retinopathy.

PURPOSE: We investigated using ultrawide-field fundus images with a deep convolutional neural networ...

Job interview training targeting nonverbal communication using an android robot for individuals with autism spectrum disorder.

Job interviews are significant barriers for individuals with autism spectrum disorder because these ...

Using natural language processing and machine learning to classify health literacy from secure messages: The ECLIPPSE study.

Limited health literacy is a barrier to optimal healthcare delivery and outcomes. Current measures r...

Discovering the Type 2 Diabetes in Electronic Health Records Using the Sparse Balanced Support Vector Machine.

The diagnosis of type 2 diabetes (T2D) at an early stage has a key role for an adequate T2D integrat...

Machine Learning Consensus To Predict the Binding to the Androgen Receptor within the CoMPARA Project.

The nuclear androgen receptor (AR) is one of the most relevant biological targets of Endocrine Disru...

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