Endocrinology

Latest AI and machine learning research in endocrinology for healthcare professionals.

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Retinal Ischemic Perivascular Lesions (RIPLs) as Potential Biomarkers for Systemic Vascular Diseases: A Narrative Review of the Literature.

Retinal ischemic perivascular lesions (RIPLs) are characteristic focal thinning of the inner nuclear...

Automatic smart brain tumor classification and prediction system using deep learning.

A brain tumor is a serious medical condition characterized by the abnormal growth of cells within th...

Enhancing Transthyretin Binding Affinity Prediction with a Consensus Model: Insights from the Tox24 Challenge.

Transthyretin (TTR) plays a vital role in thyroid hormone transport and homeostasis in both the bloo...

Modeling the number of new cases of childhood type 1 diabetes using Poisson regression and machine learning methods; a case study in Saudi Arabia.

Diabetes mellitus stands out as one of the most prevalent chronic conditions affecting pediatric pop...

Advancing Cardiovascular, Kidney, and Metabolic Medicine: A Narrative Review of Insights and Innovations for the Future.

Cardiovascular, kidney and metabolic (CKM) conditions are interrelated, significantly contributing t...

SEM model analysis of diabetic patients' acceptance of artificial intelligence for diabetic retinopathy.

AIMS: This study aimed to investigate diabetic patients' acceptance of artificial intelligence (AI) ...

Predicting isolated impaired glucose tolerance without oral glucose tolerance test using machine learning in Chinese Han men.

BACKGROUND: Isolated Impaired Glucose Tolerance (I-IGT) represents a specific prediabetic state that...

GDM-BC: Non-invasive body composition dataset for intelligent prediction of Gestational Diabetes Mellitus.

Gestational Diabetes Mellitus (GDM) refers to any degree of impaired glucose tolerance with onset or...

Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks.

Diabetic Retinopathy (DR) is a leading cause of vision impairment globally, necessitating regular sc...

The association of trimethylamine N-oxide with diabetic retinopathy Pathology: Insights from network toxicology and molecular docking analysis.

Trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite, has emerged as a potential contr...

Clinical performance of a machine learning-based model for detecting lymph node metastasis in papillary thyroid carcinoma: A multicenter study.

Papillary thyroid carcinoma (PTC) is a common endocrine malignancy with a generally favorable progno...

Diabetic retinopathy detection based on mobile maxout network and weber local descriptor feature selection using retinal fundus image.

Retinal screening provides for earlier detection of diabetic retinopathy (DR) as well as prompt diag...

A novel deep learning approach to classify 3D foot types of diabetic patients.

Diabetes mellitus is a worldwide epidemic that leads to significant changes in foot shape, deformiti...

Comparison of artificial intelligence-generated and physician-generated patient education materials on early diabetic kidney disease.

BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetes mellitus ...

Combining Ultrasound Imaging and Molecular Testing in a Multimodal Deep Learning Model for Risk Stratification of Indeterminate Thyroid Nodules.

Indeterminate cytology (Bethesda III and IV) represents 15-30% of biopsied thyroid nodules and requ...

Computational modelling for risk assessment of neurological disorder in diabetes using Hodgkin-Huxley model.

BACKGROUND: Diabetes mellitus, characterized by chronic glucose dysregulation, significantly increas...

A Deep Learning Survival Model for Evaluating the Survival Prognosis of Papillary Thyroid Cancer: A Population-Based Cohort Study.

BACKGROUND: Deep learning can assess the individual survival prognosis in sizeable datasets with int...

Deep learning model based on ultrasound images predicts BRAF V600E mutation in papillary thyroid carcinoma.

BRAF V600E mutation status detection facilitates prognosis prediction in papillary thyroid carcinoma...

Machine Learning Models for Predicting Type 2 Diabetes Complications in Malaysia.

This study aimed to develop machine learning (ML) models to predict diabetic complications in patien...

Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.

This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differe...

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