Endocrinology

Neural-Net Artificial Pancreas: A Randomized Crossover Trial of a First-in-Class Automated Insulin Delivery Algorithm.

Automated insulin delivery (AID) is now integral to the clinical practice of type 1 diabetes (T1D)....

A novel deep machine learning algorithm with dimensionality and size reduction approaches for feature elimination: thyroid cancer diagnoses with randomly missing data.

Thyroid cancer incidences endure to increase even though a large number of inspection tools have bee...

The Risks and Challenges of Artificial Intelligence in Endocrinology.

Artificial intelligence (AI) holds the promise of addressing many of the numerous challenges healthc...

Artificial Intelligence in Endocrinology: On Track Toward Great Opportunities.

In endocrinology, the types and quantity of digital data are increasing rapidly. Computing capabilit...

Deep-Learning Based Automated Segmentation and Quantitative Volumetric Analysis of Orbital Muscle and Fat for Diagnosis of Thyroid Eye Disease.

PURPOSE: Thyroid eye disease (TED) is characterized by proliferation of orbital tissues and complica...

Bibliometric analysis of research trends and hotspots on robot-assisted thyroid surgery.

BACKGROUND: Thyroid surgery involves the partial or complete removal of the thyroid gland and is a f...

Surgical Technique and Perioperative Outcomes Following Single-Port Robotic Adrenalectomy: A Single Institutional Experience.

To describe a single institution's experience with single-port robotic adrenalectomy (SP-RA) and re...

[Deep Learning-Based Key Frame Recognition Algorithm for Adrenal Vascular in X-Ray Imaging].

Adrenal vein sampling is required for the staging diagnosis of primary aldosteronism, and the frames...

StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.

MOTIVATION: Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidne...

A deep learning system for predicting time to progression of diabetic retinopathy.

Using Natural Language Processing to Extract and Classify Symptoms Among Patients with Thyroid Dysfunction.

In the United States, more than 12% of the population will experience thyroid dysfunction. Patient s...

Worldwide productivity and research trend of publications concerning intestinal polyps: A bibliometric study.

There is a significant relationship between intestinal polyps and colorectal cancer, and in recent y...

Integration of transcriptome and machine learning to identify the potential key genes and regulatory networks affecting drip loss in pork.

Low level of drip loss (DL) is an important quality characteristic of meat with high economic value....

Using deep learning to accurately detect sow vulva size in a group pen with a single camera.

This paper presents a non-contact method for the detection of changes in sow vulva size in a group p...

Federated Diabetes Prediction in Canadian Adults Using Real-world Cross-Province Primary Care Data.

Integrating Electronic Health Records (EHR) and the application of machine learning present opportun...

Enhancing Wearable Sensor Data Classification Through Novel Modified- Recurrent Plot-Based Image Representation and Mixup Augmentation.

Deep learning advancements have revolutionized scalable classification in many domains including com...

[A CASE OF TESTICULAR TUMOR UNDER CONSIDERATION FOR PARTIAL ORCHIECTOMY THROUGH RAPID INTRAOPERATIVE DIAGNOSIS].

A 35-year-old man visited a local doctor for continuing analysis of his infertility. Semen analysis ...

[CLINICAL EVALUATION OF THERAPEUTIC EFFECT PREDICTORS IN PEMBROLIZUMAB FOR ADVANCED UROTHELIAL CANCER].

(Purpose) We performed a clinical retrospective study on the evaluation of pembrolizumab treatment r...

[Artificial intelligence in ultrasound diagnosis of thyroid nodules].

OBJECTIVE: To analyze the efficacy of the S-Detect AI system of the Samsung RS85 ultrasound scanner ...

A neural network model for predicting the effectiveness of treatment in patients with neovascular glaucoma associated with diabetes mellitus.

INTRODUCTION: The study hypothesizes that neural networks can be an effective tool for predicting tr...

Corrigendum to: Super-resolution based Nodule Localization in Thyroid Ultrasound Images through Deep Learning.

The funding details have been incorporated upon author's request in the funding section of this arti...