Endocrinology

Automated Molecular Subtyping of Breast Carcinoma Using Deep Learning Techniques.

OBJECTIVE: Molecular subtyping is an important procedure for prognosis and targeted therapy of breas...

Deep Learning and Medical Image Processing Techniques for Diabetic Retinopathy: A Survey of Applications, Challenges, and Future Trends.

Diabetic retinopathy (DR) is a common eye retinal disease that is widely spread all over the world. ...

Annotation-Free Deep Learning-Based Prediction of Thyroid Molecular Cancer Biomarker BRAF (V600E) from Cytological Slides.

Thyroid cancer is the most common endocrine cancer. Papillary thyroid cancer (PTC) is the most preva...

Deep learning-based hemorrhage detection for diabetic retinopathy screening.

Diabetic retinopathy is a retinal compilation that causes visual impairment. Hemorrhage is one of th...

Investigation of optimal convolutional neural network conditions for thyroid ultrasound image analysis.

Neural network models have been used to analyze thyroid ultrasound (US) images and stratify malignan...

MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques.

BACKGROUND: Detecting brain tumors in their early stages is crucial. Brain tumors are classified by ...

Editorial: Mechanistic, machine learning and hybrid models of the "other" endocrine regulatory systems in health & disease.

Implementation of five machine learning methods to predict the 52-week blood glucose level in patients with type 2 diabetes.

OBJECTIVE: For the patients who are suffering from type 2 diabetes, blood glucose level could be aff...

A Novel Blunge Calibration Intelligent Feature Classification Model for the Prediction of Hypothyroid Disease.

According to the Indian health line report, 12% of the population suffer from abnormal thyroid funct...

Prediction of ethanol fermentation under stressed conditions using yeast morphological data.

A high sugar concentration is used as a starting condition in alcoholic fermentation by budding yeas...

Identification of Glucose Transport Modulators In Vitro and Method for Their Deep Learning Neural Network Behavioral Evaluation in Glucose Transporter 1-Deficient Mice.

Metabolic flux augmentation via glucose transport activation may be desirable in glucose transporter...

Estimation of a Machine Learning-Based Decision Rule to Reduce Hypoglycemia Among Older Adults With Type 1 Diabetes: A Post Hoc Analysis of Continuous Glucose Monitoring in the WISDM Study.

BACKGROUND: The Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study demonstrated co...

FDE-net: Frequency-domain enhancement network using dynamic-scale dilated convolution for thyroid nodule segmentation.

Thyroid nodules, a common disease of endocrine system, have a probability of nearly 10% to turn into...

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal pat...

Automatic detection of brain tumors with the aid of ensemble deep learning architectures and class activation map indicators by employing magnetic resonance images.

Today, as in every life-threatening disease, early diagnosis of brain tumors plays a life-saving rol...

Fully automatic volume measurement of the adrenal gland on CT using deep learning to classify adrenal hyperplasia.

OBJECTIVES: To develop a fully automated deep learning model for adrenal segmentation and to evaluat...

Personalized Blood Glucose Prediction for Type 1 Diabetes Using Evidential Deep Learning and Meta-Learning.

The availability of large amounts of data from continuous glucose monitoring (CGM), together with th...

Time for Using Machine Learning for Dose Guidance in Titration of People With Type 2 Diabetes? A Systematic Review of Basal Insulin Dose Guidance.

BACKGROUND: Real-world studies of people with type 2 diabetes (T2D) have shown insufficient dose adj...

Acute Intraoperative Hyperkalemia During Robot-Assisted Radical Cystectomy: A Case Report.

A 50-year-old man with muscle-invasive bladder cancer was scheduled for a robotic radical cystectomy...

Ultrasound images-based deep learning radiomics nomogram for preoperative prediction of rearrangement in papillary thyroid carcinoma.

PURPOSE: To create an ultrasound -based deep learning radiomics nomogram (DLRN) for preoperatively p...

Application of deep learning as an ancillary diagnostic tool for thyroid FNA cytology.

BACKGROUND: Several studies have used artificial intelligence (AI) to analyze cytology images, but A...