Endocrinology

Artificial intelligence based prediction models for individuals at risk of multiple diabetic complications: A systematic review of the literature.

AIM: The aim of this review is to examine the effectiveness of artificial intelligence in predicting...

Machine Learning with Neural Networks to Enhance Selectivity of Nonenzymatic Electrochemical Biosensors in Multianalyte Mixtures.

Nonenzymatic biosensors hold great potential in the field of analysis and detection due to long-term...

Machine Learning Models for Data-Driven Prediction of Diabetes by Lifestyle Type.

The prevalence of diabetes has been increasing in recent years, and previous research has found that...

Design and Usability of an Avatar-Based Learning Program to Support Diabetes Education: Quality Improvement Study in Colombia.

BACKGROUND: This quality improvement study, entitled Avatar-Based LEarning for Diabetes Optimal Cont...

Causal deep learning reveals the comparative effectiveness of antihyperglycemic treatments in poorly controlled diabetes.

Type-2 diabetes is associated with severe health outcomes, the effects of which are responsible for ...

Diseased thyroid tissue classification in OCT images using deep learning: Towards surgical decision support.

Intraoperative guidance tools for thyroid surgery based on optical coherence tomography (OCT) could ...

Brain tumor classification based on neural architecture search.

Brain tumor is a life-threatening disease and causes about 0.25 million deaths worldwide in 2020. Ma...

The new robotic platform Hugo™ RAS for lateral transabdominal adrenalectomy: a first world report of a series of five cases.

Robotic assisted surgery is the most rapidly developing field of minimally invasive surgery. Its wid...

Exploring risk factors for cervical lymph node metastasis in papillary thyroid microcarcinoma: construction of a novel population-based predictive model.

BACKGROUND: Machine learning was a highly effective tool in model construction. We aim to establish ...

A multi-granularity convolutional neural network model with temporal information and attention mechanism for efficient diabetes medical cost prediction.

As the cost of diabetes treatment continues to grow, it is critical to accurately predict the medica...

Computational model of the full-length TSH receptor.

(GPCR)The receptor for TSH receptor (TSHR), a G protein coupled receptor (GPCR), is of particular in...

Editorial Comment: ACR TI-RADS for Pediatric Thyroid Nodules on Ultrasound-A Structured Interpretation.

An automated unsupervised deep learning-based approach for diabetic retinopathy detection.

As per the International Diabetes Federation (IDF) report, 35-60% of people suffering from diabetic ...

Automated classification of estrous stage in rodents using deep learning.

The rodent estrous cycle modulates a range of biological functions, from gene expression to behavior...

An overview of deep learning applications in precocious puberty and thyroid dysfunction.

In the last decade, deep learning methods have garnered a great deal of attention in endocrinology r...

Thyroid Nodules on Ultrasound in Children and Young Adults: Comparison of Diagnostic Performance of Radiologists' Impressions, ACR TI-RADS, and a Deep Learning Algorithm.

In current clinical practice, thyroid nodules in children are generally evaluated on the basis of r...

A wearable soft robot that can alleviate the pain and fear of the wearer.

Social soft robotics may provide a new solution for alleviating human pain and fear. Here, we introd...

A Matched-Pair Analysis of Nuclear Morphologic Features Between Core Needle Biopsy and Surgical Specimen in Thyroid Tumors Using a Deep Learning Model.

Core needle biopsy (CNB) is a method that can be used as an alternative to fine-needle aspiration fo...

Predicting risk of obesity and meal planning to reduce the obese in adulthood using artificial intelligence.

BACKGROUND: An unhealthy diet or excessive amount of food intake creates obesity issues in human bei...

Predictive Analysis of Diabetes-Risk with Class Imbalance.

Diabetes type 2 (T2DM) is a common chronic disease, increasingly leading to many complications and a...

Longitudinal deep learning clustering of Type 2 Diabetes Mellitus trajectories using routinely collected health records.

Type 2 diabetes mellitus (T2DM) is a highly heterogeneous chronic disease with different pathophysio...