Endocrinology

Hyperthyroidism treatment by alternative therapies based on cupping and dietary-herbal supplementation: a case report.

OBJECTIVES: Hyperthyroidism is characterized by increasing production of thyroid hormone (TH) and decreasing of thyroid stimulation hormone (TSH) secretion. The treatment of hyperthyroidism includes such as anti-thyroid drugs, radioiodine, and thyroidectomy have many side effects without complete curing results. We described a successful treatment of hyperthyroidism patient with dietary-herbal sup...

MR-Based Radiomics for Differential Diagnosis between Cystic Pituitary Adenoma and Rathke Cleft Cyst.

BACKGROUND: It is often tricky to differentiate cystic pituitary adenoma from Rathke cleft cyst with visual inspection because of similar MRI presentations between them. We aimed to design an MR-based radiomics model for improving differential diagnosis between them.

Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study.

Given the rapid increase in the incidence of cardiometabolic conditions, there is an urgent need for better approaches to prevent as many cases as pos...

Neovascularization Detection and Localization in Fundus Images Using Deep Learning.

Proliferative Diabetic Retinopathy (PDR) is a severe retinal disease that threatens diabetic patients. It is characterized by neovascularization in th...

A concise review: the synergy between artificial intelligence and biomedical nanomaterials that empowers nanomedicine.

Nanomedicine has recently experienced unprecedented growth and development. However, the complexity of operations at the nanoscale introduces a layer ...

Application of Pet-CT Fusion Deep Learning Imaging in Precise Radiotherapy of Thyroid Cancer.

This article explores the value of wall F-FDG PET/Cr imaging in the diagnosis of thyroid cancer, studies its ability to distinguish benign and maligna...

Real-world artificial intelligence-based opportunistic screening for diabetic retinopathy in endocrinology and indigenous healthcare settings in Australia.

This study investigated the diagnostic performance, feasibility, and end-user experiences of an artificial intelligence (AI)-assisted diabetic retinop...

Development and validation of a new diabetes index for the risk classification of present and new-onset diabetes: multicohort study.

In this study, we aimed to propose a novel diabetes index for the risk classification based on machine learning techniques with a high accuracy for di...

CAFT: a deep learning-based comprehensive abdominal fat analysis tool for large cohort studies.

BACKGROUND: There is increasing appreciation of the association of obesity beyond co-morbidities, such as cancers, Type 2 diabetes, hypertension, and ...

Simultaneous brain structure segmentation in magnetic resonance images using deep convolutional neural networks.

In brain magnetic resonance imaging (MRI) examinations, rapidly acquired two-dimensional (2D) T1-weighted sagittal slices are typically used to confir...

A stacking ensemble deep learning approach to cancer type classification based on TCGA data.

Cancer tumor classification based on morphological characteristics alone has been shown to have serious limitations. Breast, lung, colorectal, thyroid...

Characterization of Ultra-Widefield Angiographic Vascular Features in Diabetic Retinopathy with Automated Severity Classification.

PURPOSE: To determine the association between diabetic retinopathy (DR) severity and quantitative retinal vascular features.

Deep Learning for Diabetes: A Systematic Review.

Diabetes is a chronic metabolic disorder that affects an estimated 463 million people worldwide. Aiming to improve the treatment of people with diabet...

Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models.

Type 1 diabetes is a chronic disease caused by the inability of the pancreas to produce insulin. Patients suffering type 1 diabetes depend on the appr...

Generalizability of heterogeneous treatment effects based on causal forests applied to two randomized clinical trials of intensive glycemic control.

Purpose Machine learning is an attractive tool for identifying heterogeneous treatment effects (HTE) of interventions but generalizability of machine ...

Robotics and future technical developments in pediatric urology.

Minimally invasive surgery (MIS) has represented the main innovation in the field of pediatric surgery and urology over the last 30 years. Pediatric M...

Economic Evaluations of Artificial Intelligence in Ophthalmology.

Artificial intelligence (AI) is expected to cause significant medical quality enhancements and cost-saving improvements in ophthalmology. Although the...

An interpretable multiple-instance approach for the detection of referable diabetic retinopathy in fundus images.

Diabetic retinopathy (DR) is one of the leading causes of vision loss across the world. Yet despite its wide prevalence, the majority of affected peop...

Prediction model for thyrotoxic atrial fibrillation: a retrospective study.

BACKGROUND: Thyrotoxic atrial fibrillation (TAF) is a recognized significant complication of hyperthyroidism. Early identification of the individuals ...

Deep learning-based automated detection for diabetic retinopathy and diabetic macular oedema in retinal fundus photographs.

OBJECTIVES: To present and validate a deep ensemble algorithm to detect diabetic retinopathy (DR) and diabetic macular oedema (DMO) using retinal fund...