Endocrinology

Integrating artificial intelligence (S-Detect software) and contrast-enhanced ultrasound for enhanced diagnosis of thyroid nodules: A comprehensive evaluation study.

PURPOSE: This study aims to assess the diagnostic efficacy of Korean Thyroid imaging reporting and d...

Long-term Major Adverse Cardiac Event Prediction by Computed Tomography-derived Plaque Measures and Clinical Parameters Using Machine Learning.

Objective The present study evaluated the usefulness of machine learning (ML) models with the corona...

The impact of deep learning on diagnostic performance in the differentiation of benign and malignant thyroid nodules.

AIMS: This study aims to use deep learning (DL) to classify thyroid nodules as benign and malignant ...

Histopathologic Differential Diagnosis and Estrogen Receptor/Progesterone Receptor Immunohistochemical Evaluation of Breast Carcinoma Using a Deep Learning-Based Artificial Intelligence Architecture.

In breast carcinoma, invasive ductal carcinoma (IDC) is the most common histopathologic subtype, and...

Comparison of Machine Learning Algorithms and Nomogram Construction for Diabetic Retinopathy Prediction in Type 2 Diabetes Mellitus Patients.

INTRODUCTION: The aim of this study was to compare various machine learning algorithms for construct...

Deep Hair Phenomics: Implications in Endocrinology, Development, and Aging.

Hair quality is an important indicator of health in humans and other animals. Current approaches to ...

Deep-Learning-Based Blood Glucose Detection Device Using Acetone Exhaled Breath Sensing Features of α-FeO-MWCNT Nanocomposites.

Owing to the correlation between acetone in human's exhaled breath (EB) and blood glucose, the devel...

Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.

BACKGROUND: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipos...

Knowledge-based machine learning for predicting and understanding the androgen receptor (AR)-mediated reproductive toxicity in zebrafish.

Traditional methods for identifying endocrine-disrupting chemicals (EDCs) that activate androgen rec...

Predicting Response to Neuromodulators or Prokinetics in Patients With Suspected Gastroparesis Using Machine Learning: The "BMI, Infectious Prodrome, Delayed GES, and No Diabetes" Model.

INTRODUCTION: Pharmacologic therapies for symptoms of gastroparesis (GP) have limited efficacy, and ...

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning (Diabetes Metab J 2024;48:771-9).

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning (Diabetes Metab J 2024;48:771-9).

Deciphering Dormant Cells of Lung Adenocarcinoma: Prognostic Insights from O-glycosylation-Related Tumor Dormancy Genes Using Machine Learning.

Lung adenocarcinoma (LUAD) poses significant challenges due to its complex biological characteristic...

The early prediction of gestational diabetes mellitus by machine learning models.

BACKGROUND: We aimed to determine the best-performing machine learning (ML)-based algorithm for pred...

Pathology diagnosis of intraoperative frozen thyroid lesions assisted by deep learning.

BACKGROUND: Thyroid cancer is a common thyroid malignancy. The majority of thyroid lesion needs intr...

Prediction model for lateral lymph node metastasis of papillary thyroid carcinoma in children and adolescents based on ultrasound imaging and clinical features: a retrospective study.

BACKGROUND: The presence of lateral lymph node metastases (LNM) in paediatric patients with papillar...

Optimized deep CNN for detection and classification of diabetic retinopathy and diabetic macular edema.

Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominen...

Development of oculomics artificial intelligence for cardiovascular risk factors: A case study in fundus oculomics for HbA1c assessment and clinically relevant considerations for clinicians.

Artificial Intelligence (AI) is transforming healthcare, notably in ophthalmology, where its ability...

Twistable and Stretchable Nasal Patch for Monitoring Sleep-Related Breathing Disorders Based on a Stacking Ensemble Learning Model.

Obstructive sleep apnea syndrome disrupts sleep, destroys the homeostasis of biological systems such...

Artificial neural network prediction of postoperative complications in papillary thyroid microcarcinoma based on preoperative ultrasonographic features.

OBJECTIVE: To predict post-thyroidectomy complications in papillary thyroid microcarcinoma (PTMC) pa...

Use of Natural Language Processing to Extract and Classify Papillary Thyroid Cancer Features From Surgical Pathology Reports.

BACKGROUND: We aim to use Natural Language Processing to automate the extraction and classification ...