Endocrinology

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

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Machine learning to predict the occurrence of thyroid nodules: towards a quantitative approach for judicious utilization of thyroid ultrasonography.

INTRODUCTION: Ultrasound is instrumental in the early detection of thyroid nodules, which is crucial...

Model-Informed Precision Dosing Using Machine Learning for Levothyroxine in General Practice: Development, Validation and Clinical Simulation Trial.

Levothyroxine is one of the most prescribed drugs in the western world. Dosing is challenging due to...

Microstrip isoelectric focusing with deep learning for simultaneous screening of diabetes, anemia, and thalassemia.

BACKGROUND: Hemoglobin (Hb) is an important protein in red blood cells and a crucial diagnostic indi...

SSiT: Saliency-Guided Self-Supervised Image Transformer for Diabetic Retinopathy Grading.

Self-supervised Learning (SSL) has been widely applied to learn image representations through exploi...

Optimizing removal of antiretroviral drugs from tertiary wastewater using chlorination and AI-based prediction with response surface methodology.

Chemical and pharmaceutical chemicals found in water sources create substantial risks to human healt...

Enhanced thyroid nodule segmentation through U-Net and VGG16 fusion with feature engineering: A comprehensive study.

BACKGROUND AND OBJECTIVE: The thyroid gland, a key component of the endocrine system, is pivotal in ...

Pre-hospital glycemia as a biomarker for in-hospital all-cause mortality in diabetic patients - a pilot study.

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) presents a significant healthcare challenge, with consid...

Semi-Supervised Thyroid Nodule Detection in Ultrasound Videos.

Deep learning techniques have been investigated for the computer-aided diagnosis of thyroid nodules ...

Identifying Main Themes in Diabetes Management Interviews Using Natural Language Processing-Based Text Mining.

This study aimed to identify the main themes from exit interviews of adult patients with type 2 diab...

Recognition of diabetic retinopathy and macular edema using deep learning.

Diabetic retinopathy (DR) and diabetic macular edema (DME) are both serious eye conditions associate...

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.

BACKGRUOUND: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long...

Construction and evaluation of a metabolic correlation diagnostic model for diabetes based on machine learning algorithms.

BACKGROUND: Diabetes mellitus (DM) is a prevalent chronic disease marked by significant metabolic dy...

Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks.

Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial...

Artificial intelligence assists identification and pathologic classification of glomerular lesions in patients with diabetic nephropathy.

BACKGROUND: Glomerular lesions are the main injuries of diabetic nephropathy (DN) and are used as a ...

The role of machine learning in advancing diabetic foot: a review.

BACKGROUND: Diabetic foot complications impose a significant strain on healthcare systems worldwide,...

Multi-level brain tumor classification using hybrid coot flamingo search optimization Algorithm Enabled deep learning with MRI images.

An innovative multi-level BT classification approach based on deep learning has been proposed in thi...

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets.

Type 1 diabetes (T1D) is a chronic condition in which beta cells are destroyed by immune cells. Desp...

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