Endocrinology

Deep Physiological Model for Blood Glucose Prediction in T1DM Patients.

Accurate estimations for the near future levels of blood glucose are crucial for Type 1 Diabetes Mel...

A deep learning approach based on convolutional LSTM for detecting diabetes.

Diabetes is a chronic disease that occurs when the pancreas does not generate sufficient insulin or ...

Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors.

Wearable continuous glucose monitoring (CGM) sensors are revolutionizing the treatment of type 1 dia...

Fatal case of hospital-acquired hypernatraemia in a neonate: lessons learned from a tragic error.

A 3-week-old boy with viral gastroenteritis was by error given 200 mL 1 mmol/mL hypertonic saline in...

Near-optimal insulin treatment for diabetes patients: A machine learning approach.

Blood glycemic control is crucial for minimizing severe side effects in diabetes mellitus. Currently...

Interactive thyroid whole slide image diagnostic system using deep representation.

BACKGROUND AND OBJECTIVES: The vast size of the histopathology whole slide image poses formidable ch...

Evaluation of a deep learning-based computer-aided diagnosis system for distinguishing benign from malignant thyroid nodules in ultrasound images.

PURPOSE: Computer-aided diagnosis (CAD) systems assist in solving subjective diagnosis problems that...

Therapeutic Equivalence of a New Preparation of Liquid Levothyroxine with Tablets in Patients with Overt Primary Hypothyroidism.

BACKGROUND: A new liquid levothyroxine (LT4) dissolved in glycerol and water has recently been devel...

Prediction of response to anti-vascular endothelial growth factor treatment in diabetic macular oedema using an optical coherence tomography-based machine learning method.

PURPOSE: To predict the anti-vascular endothelial growth factor (VEGF) therapeutic response of diabe...

Exploring the mechanism of TCM formulae in the treatment of different types of coronary heart disease by network pharmacology and machining learning.

Traditional Chinese medicine (TCM) has long been used in the clinical treatment of coronary heart di...

Ensemble Deep Learning Model for Multicenter Classification of Thyroid Nodules on Ultrasound Images.

BACKGROUND Thyroid nodules are extremely common and typically diagnosed with ultrasound whether beni...

Use of Machine Learning and Hybrid Closed Loop Insulin Delivery at Diabetes Camps.

Internet of things-inspired healthcare system for urine-based diabetes prediction.

Healthcare industry is the leading domain that has been revolutionized by the incorporation of Inter...

Improving blood glucose level predictability using machine learning.

This study was designed to improve blood glucose level predictability and future hypoglycemic and hy...

Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.

Type 1 diabetes (T1D) is a chronic health condition resulting from pancreatic beta cell dysfunction ...

An artificial intelligence decision support system for the management of type 1 diabetes.

Type 1 diabetes (T1D) is characterized by pancreatic beta cell dysfunction and insulin depletion. Ov...

Effect of congenital adrenal hyperplasia treated by glucocorticoids on plasma metabolome: a machine-learning-based analysis.

BACKGROUND: Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency leads to impaired ...

Classification of hyperspectral endocrine tissue images using support vector machines.

BACKGROUND: Thyroidectomy is one of the most commonly performed surgical procedures. The region of t...

Application of Artificial Intelligence in Diabetes Education and Management: Present Status and Promising Prospect.

Despite the rapid development of science and technology in healthcare, diabetes remains an incurable...

Forecasting tuberculosis using diabetes-related google trends data.

Online activity-based data can be used to aid infectious disease forecasting. Our aim was to exploit...

Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study.

To identify the most important factors that impact brain volume, while accounting for potential coll...