Endocrinology

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

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Enhancement of Detection of Diabetic Retinopathy Using Harris Hawks Optimization with Deep Learning Model.

In today's world, diabetic retinopathy is a very severe health issue, which is affecting many humans...

Feature discretization-based deep clustering for thyroid ultrasound image feature extraction.

Ultrasound imaging technology has the advantage of being convenient, less harmful and widely applied...

Classification of Thyroid Nodules by Using Deep Learning Radiomics Based on Ultrasound Dynamic Video.

OBJECTIVES: We aimed to design a radiomics model for differential diagnosis of thyroid carcinoma bas...

Diagnostic accuracy of code-free deep learning for detection and evaluation of posterior capsule opacification.

OBJECTIVE: To train and validate a code-free deep learning system (CFDLS) on classifying high-resolu...

A computer-aided diagnosis system for detecting various diabetic retinopathy grades based on a hybrid deep learning technique.

Diabetic retinopathy (DR) is a serious disease that may cause vision loss unawares without any alarm...

A deep learning-based approach for the diagnosis of adrenal adenoma: a new trial using CT.

OBJECTIVE: To develop and validate deep convolutional neural network (DCNN) models for the diagnosis...

Deep learning algorithms for detection of diabetic macular edema in OCT images: A systematic review and meta-analysis.

PURPOSE: Artificial intelligence (AI) can detect diabetic macular edema (DME) from optical coherence...

Dietary administration of D-chiro-inositol attenuates sex-specific metabolic imbalances in the 5xFAD mouse model of Alzheimer's disease.

Increasing evidence shows that hypothalamic dysfunction, insulin resistance, and weight loss precede...

Comprehensive Clinical Evaluation of a Deep Learning-Accelerated, Single-Breath-Hold Abdominal HASTE at 1.5 T and 3 T.

To evaluate the clinical performance of a deep learning-accelerated single-breath-hold half-Fourier ...

Deduction learning for precise noninvasive measurements of blood glucose with a dozen rounds of data for model training.

Personalized modeling has long been anticipated to approach precise noninvasive blood glucose measur...

A Novel Approach for Feature Selection and Classification of Diabetes Mellitus: Machine Learning Methods.

An active research area where the experts from the medical field are trying to envisage the problem ...

Robot-enhanced diabetes care for middle-aged and older adults living with diabetes in the community: A small sample size mixed-method evaluation.

PURPOSE: This study assessed robot-enhanced healthcare in practical settings for the purpose of comm...

Optimization and Evaluation of an Intelligent Short-Term Blood Glucose Prediction Model Based on Noninvasive Monitoring and Deep Learning Techniques.

Continuous noninvasive blood glucose monitoring and estimation management by using photoplethysmogra...

Fully Automated Abdominal CT Biomarkers for Type 2 Diabetes Using Deep Learning.

Background CT biomarkers both inside and outside the pancreas can potentially be used to diagnose ty...

Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review.

BACKGROUND: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer impose...

Reducing prediction volatility in the surgical workflow recognition of endoscopic pituitary surgery.

PURPOSE: Workflow recognition can aid surgeons before an operation when used as a training tool, dur...

Detection of signs of disease in external photographs of the eyes via deep learning.

Retinal fundus photographs can be used to detect a range of retinal conditions. Here we show that de...

Deep learning approach identified a gene signature predictive of the severity of renal damage caused by chronic cadmium accumulation.

Epidemiology studies have indicated that environmental cadmium exposure, even at low levels, will re...

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