Endocrinology

Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach.

BACKGROUND AND PURPOSE: Spontaneous intracranial hypotension is an increasingly recognized condition...

Application of machine learning in affordable and accessible insulin management for type 1 and 2 diabetes: A comprehensive review.

Proper insulin management is vital for maintaining stable blood sugar levels and preventing complica...

Deep learning-based computer-aided diagnosis system for the automatic detection and classification of lateral cervical lymph nodes on original ultrasound images of papillary thyroid carcinoma: a prospective diagnostic study.

PURPOSE: This study aims to develop a deep learning-based computer-aided diagnosis (CAD) system for ...

Attention-based deep learning framework for automatic fundus image processing to aid in diabetic retinopathy grading.

BACKGROUND AND OBJECTIVE: Early detection and grading of Diabetic Retinopathy (DR) is essential to d...

The application value of deep learning-based nomograms in benign-malignant discrimination of TI-RADS category 4 thyroid nodules.

Thyroid nodules are a common occurrence, and although most are non-cancerous, some can be malignant....

[Artificial intelligence and screening for visual impairment related to diabetic retinopathy and macular edema].

Artificial intelligence facial recognition system for diagnosis of endocrine and metabolic syndromes based on a facial image database.

AIM: To build a facial image database and to explore the diagnostic efficacy and influencing factors...

Artificial intelligence based glaucoma and diabetic retinopathy detection using MATLAB - retrained AlexNet convolutional neural network.

BACKGROUND: Glaucoma and diabetic retinopathy (DR) are the leading causes of irreversible retinal da...

[Involvement of essential trace elements in the pathogenesis of thyroid diseases: diagnostic markers and analytical methods for determination].

AIM: To study the role of iodine, selenium and zinc in the pathogenesis of iodine deficiency and aut...

An ensemble deep learning diagnostic system for determining Clinical Activity Scores in thyroid-associated ophthalmopathy: integrating multi-view multimodal images from anterior segment slit-lamp photographs and facial images.

BACKGROUND: Thyroid-associated ophthalmopathy (TAO) is the most prevalent autoimmune orbital conditi...

Identifying gray matter alterations in Cushing's disease using machine learning: An interpretable approach.

BACKGROUND: Cushing's Disease (CD) is a rare clinical syndrome characterized by excessive secretion ...

Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge.

Leveraging continuous glucose monitoring (CGM) systems, real-time blood glucose (BG) forecasting is ...

Expansion of thyroid surgical territory through 10,000 cases under the da Vinci robotic knife.

With the progress of robotic transaxillary thyroid surgery (RTTS), the indications for this procedur...

Wearable Movement Exploration Device with Machine Learning Algorithm for Screening and Tracking Diabetic Neuropathy-A Cross-Sectional, Diagnostic, Comparative Study.

BACKGROUND: Diabetic neuropathy is one of the most common complications of diabetes mellitus. The ai...

Predicting central cervical lymph node metastasis in papillary thyroid microcarcinoma using deep learning.

BACKGROUND: The aim of this study is to design a deep learning (DL) model to preoperatively predict ...

A systematic review of machine learning based thyroid tumor characterisation using ultrasonographic images.

Ultrasonography is widely used to screen thyroid tumors because it is safe, easy to use, and low-cos...

Employing deep learning and transfer learning for accurate brain tumor detection.

Artificial intelligence-powered deep learning methods are being used to diagnose brain tumors with h...

Self-supervised category selective attention classifier network for diabetic macular edema classification.

AIMS: This study aims to develop an advanced model for the classification of Diabetic Macular Edema ...

Comparative performance analysis of Boruta, SHAP, and Borutashap for disease diagnosis: A study with multiple machine learning algorithms.

Interpretable machine learning models are instrumental in disease diagnosis and clinical decision-ma...

Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes.

OBJECTIVE: This study aims to explore the opinions on the insurance coverage of artificial intellige...

Screening/diagnosis of pediatric endocrine disorders through the artificial intelligence model in different language settings.

UNLABELLED: This study is aimed at examining the impact of ChatGPT on pediatric endocrine and metabo...