Endocrinology

Updates of precision medicine in type 2 diabetes.

Diabetes mellitus is prevalent worldwide and affects 1 in 10 adults. Despite the successful development of glucose-lowering drugs, such as glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 inhibitors recently, the proportion of patients achieving satisfactory glucose control has not risen as expected. The heterogeneity of diabetes determines that a one-size-fits-...

A deep learning nomogram of continuous glucose monitoring data for the risk prediction of diabetic retinopathy in type 2 diabetes.

Continuous glucose monitoring (CGM) data analysis will provide a new perspective to analyze factors related to diabetic retinopathy (DR). However, the problem of visualizing CGM data and automatically predicting the incidence of DR from CGM is still controversial. Here, we explored the feasibility of using CGM profiles to predict DR in type 2 diabetes (T2D) by deep learning approach. This study fu...

Facelift thyroid surgery: a systematic review of indications, surgical and functional outcomes.

OBJECTIVE: To investigate indications, surgical and functional outcomes of robotic or endoscopic facelift thyroid surgery (FTS) and whether FTS report...

A Novel Deep-Learning-Based CADx Architecture for Classification of Thyroid Nodules Using Ultrasound Images.

Nodules of thyroid cancer occur in the cells of the thyroid as benign or malign types. Thyroid sonographic images are mostly used for diagnosis of thy...

Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records.

Background Statins are guideline-recommended medications that reduce cardiovascular events in patients with diabetes. Yet, statin use is concerningly ...

Deep Learning-Enabled Morphometric Analysis for Toxicity Screening Using Zebrafish Larvae.

Toxicology studies heavily rely on morphometric analysis to detect abnormalities and diagnose disease processes. The emergence of ever-increasing vari...

Preoperative endogenous total testosterone predicts prostate cancer progression: results in 580 consecutive patients treated with robot assisted radical prostatectomy for clinically localized disease.

PURPOSE: To test the role of endogenous total testosterone (ETT) as a predictor of prostate cancer (PCa) progression in patients treated with robot as...

Efficacy and Safety of Minimally Invasive Thyroid Surgery: A Network Meta-Analysis.

OBJECTIVES: Minimally invasive and remote surgical approaches for thyroid tumors have been developed primarily for cosmetic benefit. However, conventi...

Deep Learning Prediction of Promoter Mutation Status in Thyroid Cancer Using Histologic Images.

objectives: Telomerase reverse transcriptase () promoter mutation, found in a subset of patients with thyroid cancer, is strongly associated with agg...

A Federated Learning-Inspired Evolutionary Algorithm: Application to Glucose Prediction.

In this paper, we propose an innovative Federated Learning-inspired evolutionary framework. Its main novelty is that this is the first time that an Ev...

Prescribing patterns of SGLT-2 inhibitors for patients with heart failure: A two-center analysis.

BACKGROUND: Sodium glucose co-transporter 2 inhibitors (SGLT2i) have been proven to reduce the combined risk of cardiovascular death and hospitalizati...

Machine learning to improve false-positive results in the Dutch newborn screening for congenital hypothyroidism.

OBJECTIVE: The Dutch Congenital hypothyroidism (CH) Newborn Screening (NBS) algorithm for thyroidal and central congenital hypothyroidism (CH-T and CH...

3D Ultrasound Reconstructions of the Carotid Artery and Thyroid Gland Using Artificial-Intelligence-Based Automatic Segmentation-Qualitative and Quantitative Evaluation of the Segmentation Results via Comparison with CT Angiography.

The aim of this study was to evaluate the feasibility of a noninvasive and low-operator-dependent imaging method for carotid-artery-stenosis diagnosis...

Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques.

The study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and reduce unnecessary oral glucose tolerance test (O...

Remote-access robotic thyroidectomy: A systematic review.

BACKGROUND: Recently, robotic surgery has been introduced as a new surgical approach to the thyroid.

GPCRLigNet: rapid screening for GPCR active ligands using machine learning.

Molecules with bioactivity towards G protein-coupled receptors represent a subset of the vast space of small drug-like molecules. Here, we compare mac...

Deep-learning-based prognostic modeling for incident heart failure in patients with diabetes using electronic health records: A retrospective cohort study.

Patients with type 2 diabetes mellitus (T2DM) have more than twice the risk of developing heart failure (HF) compared to patients without diabetes. Th...

An integrated nomogram combining deep learning, clinical characteristics and ultrasound features for predicting central lymph node metastasis in papillary thyroid cancer: A multicenter study.

OBJECTIVE: Central lymph node metastasis (CLNM) is a predictor of poor prognosis for papillary thyroid carcinoma (PTC) patients. The options for surge...

PatchResNet: Multiple Patch Division-Based Deep Feature Fusion Framework for Brain Tumor Classification Using MRI Images.

Modern computer vision algorithms are based on convolutional neural networks (CNNs), and both end-to-end learning and transfer learning modes have bee...

The impact of diabetes mellitus on pelvic organ prolapse recurrence after robotic sacrocolpopexy.

INTRODUCTION AND HYPOTHESIS: Data examining the effect of diabetes mellitus (DM) on prolapse recurrence after sacrocolpopexy (SCP) is limited. The pri...