Endocrinology

Deep learning for automated detection of neovascular leakage on ultra-widefield fluorescein angiography in diabetic retinopathy.

Diabetic retinopathy is a leading cause of blindness in working-age adults worldwide. Neovascular leakage on fluorescein angiography indicates progression to the proliferative stage of diabetic retinopathy, which is an important distinction that requires timely ophthalmic intervention with laser or intravitreal injection treatment to reduce the risk of severe, permanent vision loss. In this study,...

Graph-based clinical recommender: Predicting specialists procedure orders using graph representation learning.

OBJECTIVE: To determine whether graph neural network based models of electronic health records can predict specialty consultation care needs for endocrinology and hematology more accurately than the standard of care checklists and other conventional medical recommendation algorithms in the literature.

A diabetes prediction model based on Boruta feature selection and ensemble learning.

BACKGROUND AND OBJECTIVE: As a common chronic disease, diabetes is called the "second killer" among modern diseases. Currently, there is no medical cu...

Elevated Plasma Levels of MT4-MMP and MT6-MMP; A New Observation in Patients with Thyroid Nodules.

BACKGROUND: Based on the critical role of MT4-MMP and MT6-MMP in carcinogenesis, we focused on MT4-MMP and MT6-MMP circulating levels in patients with...

An Assessment of How Clinicians and Staff Members Use a Diabetes Artificial Intelligence Prediction Tool: Mixed Methods Study.

BACKGROUND: Nearly one-third of patients with diabetes are poorly controlled (hemoglobin A≥9%). Identifying at-risk individuals and providing them wit...

Three-Port Transoral Robotic Thyroidectomy in Papillary Thyroid Carcinoma.

BACKGROUND: Although transoral thyroidectomy has become popular in thyroid surgery, transoral robotic thyroidectomy (TORT) has only been successfully ...

Machine Learning-Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognition in Type 1 Diabetes Management: Development and Validation Study.

BACKGROUND: Continuous glucose monitoring (CGM) for diabetes combines noninvasive glucose biosensors, continuous monitoring, cloud computing, and anal...

The Etiology of Abnormal TSH in Veterans Cared by a VA Medical Center - One High Serum Thyrotropin is Associated with Higher 5-Years Mortality.

OBJECTIVE: By analyzing the etiology of abnormal TSH in randomly selected veteran patients, we set our heart on improving future clinical care/managem...

Rapid and precise detection of cancers via label-free SERS and deep learning.

Early, express, and reliable detection of cancer can provide a favorable prognosis and decrease mortality. Tumor biomarkers have been proven to be clo...

Artificial intelligence-based prediction of cervical lymph node metastasis in papillary thyroid cancer with CT.

OBJECTIVES: To develop an artificial intelligence (AI) system for predicting cervical lymph node metastasis (CLNM) preoperatively in patients with pap...

Comparison of surgical completeness in patients operated on conventional open total thyroidectomy (OT) or trans-axillary robot-assisted total thyroidectomy (RATT) by a single axillary approach.

Trans-axillary robot-assisted total thyroidectomy (RATT) is nowadays worldwide accepted but the completeness obtained by RATT is still debated. The Ai...

Editorial: Artificial intelligence for data discovery and reuse in endocrinology and metabolism.

Deep Learning vs Traditional Models for Predicting Hospital Readmission among Patients with Diabetes.

A hospital readmission risk prediction tool for patients with diabetes based on electronic health record (EHR) data is needed. The optimal modeling ap...

Differential diagnosis of secondary hypertension based on deep learning.

Secondary hypertension is associated with higher risks of target organ damage and cardiovascular and cerebrovascular disease events. Early aetiology i...

Adrenal lesion classification with abdomen caps and the effect of ROI size.

Accurate classification of adrenal lesions on magnetic resonance (MR) images are very important for diagnosis and treatment planning. The detection an...

A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization.

Microscopic examination of pathology slides is essential to disease diagnosis and biomedical research. However, traditional manual examination of tiss...

Deep learning for classification of thyroid nodules on ultrasound: validation on an independent dataset.

OBJECTIVES: The purpose is to apply a previously validated deep learning algorithm to a new thyroid nodule ultrasound image dataset and compare its pe...

Predictors of Remission of Acromegaly following Surgical Treatment in Growth Hormone-Secreting Pituitary Adenoma.

 Surgery is the treatment of choice for growth hormone (GH)-secreting pituitary adenoma. The remission of random GH depends on various factors. We ai...

Oncocytic adrenocortical neoplasm of borderline uncertain malignant potential diagnosed after robot-assisted adrenalectomy case report.

BACKGROUND: Adrenal incidentalomas are radiologically discovered tumors that represent a variety of pathologies, with the diagnosis clinched only on s...

Segmentation of thyroid glands and nodules in ultrasound images using the improved U-Net architecture.

BACKGROUND: Identifying thyroid nodules' boundaries is crucial for making an accurate clinical assessment. However, manual segmentation is time-consum...