Endocrinology

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

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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...

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...

Applications of Deep Learning in Endocrine Neoplasms.

Machine learning methods have been growing in prominence across all areas of medicine. In pathology,...

Deep learning-based image reconstruction improves radiologic evaluation of pituitary axis and cavernous sinus invasion in pituitary adenoma.

PURPOSE: To compare performance of 1-mm deep learning reconstruction (DLR) with 3-mm routine MRI ima...

A Machine Learning Model for Prediction of Amputation in Diabetics.

BACKGROUND: Diabetic foot ulcer (DFU) and the resulting lower extremity amputation are associated wi...

Quantitative measurement of blood glucose influenced by multiple factors via photoacoustic technique combined with optimized wavelet neural networks.

In this work, the photoacoustic (PA) quantitative measurement of blood glucose concentration (BGC) i...

Diabetes disease detection and classification on Indian demographic and health survey data using machine learning methods.

BACKGROUND & AIM: Diabetes mellitus has become one of the out brakes causing major health issues in ...

A regression-based machine learning approach for pH and glucose detection with redox-sensitive colorimetric paper sensors.

Colorimetric paper sensors are used in various fields due to their convenience and intuitive manner....

Artificial intelligence model with deep learning in nonalcoholic fatty liver disease diagnosis: genetic based artificial neural networks.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease i...

Comparative Analysis of Laparoscopic and Robotic Transperitoneal Adrenalectomy Performed at a Single Institution.

Background and Objectives: Laparoscopic adrenalectomy (LA) is the standard surgical approach for adr...

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