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Endocrinology Subcategories: Diabetes Menopause Osteoporosis Steroids Thyroid

Showing 2941-2961 of 3,475 articles

Machine learning-based coronary heart disease diagnosis model for type 2 diabetes patients.

BACKGROUND: To establish a classification model for assisting the diagnosis of type 2 diabetes melli...

Jan 2025 40475993

SMART (artificial intelligence enabled) DROP (diabetic retinopathy outcomes and pathways): Study protocol for diabetic retinopathy management.

INTRODUCTION: Delayed diagnosis of diabetic retinopathy (DR) remains a significant challenge, often ...

Jan 2025 40388448

Using Machine Learning and Artificial Intelligence to Predict Diabetes Mellitus among Women Population.

BACKGROUND: Diabetes Mellitus is a chronic health condition (long-lasting) due to inadequate control...

Jan 2025 37282643

Machine Learning and Augmented Intelligence Enables Prognosis of Type 2 Diabetes Prior to Clinical Manifestation.

BACKGROUND: The global incidence of type 2 diabetes (T2D) persists at epidemic proportions. Early di...

Jan 2025 38303524

Continuous glucose monitoring using machine learning models and IoT device data: A meta-analysis.

BACKGROUND: Machine learning offers diverse options for effectively managing blood glucose levels in...

Jan 2025 39269871

SwinDFU-Net: Deep learning transformer network for infection identification in diabetic foot ulcer.

BACKGROUND: The identification of infection in diabetic foot ulcers (DFUs) is challenging due to var...

Jan 2025 39269872

Enhancing Transfer Learning for Medical Image Classification with SMOTE: A Comparative Study

This paper explores and enhances the application of Transfer Learning (TL) for multilabel image cl...

Dec 2024 http://arxiv.org/abs/2412.20235v1

A Comparative Study on Machine Learning Models to Classify Diseases Based on Patient Behaviour and Habits

In recent years, ML algorithms have been shown to be useful for predicting diseases based on healt...

Dec 2024 http://arxiv.org/abs/2412.16768v1

Homogenization of Ordinary Differential Equations for the Fast Prediction of Diabetes Progression

The impact of physical activity on a person's progression to type 2 diabetes is multifaceted. Syst...

Dec 2024 http://arxiv.org/abs/2412.16261v1

Risk prediction of integrated traditional Chinese and western medicine for diabetes retinopathy based on optimized gradient boosting classifier model.

In order to take full advantage of traditional Chinese medicine (TCM) and western medicine, combined...

Dec 2024 39705459

Advances in Artificial Intelligence forDiabetes Prediction: Insights from a Systematic Literature Review

This systematic review explores the use of machine learning (ML) in predicting diabetes, focusing ...

Dec 2024 http://arxiv.org/abs/2412.14736v1

Deep Learning-Based Noninvasive Screening of Type 2 Diabetes with Chest X-ray Images and Electronic Health Records

The imperative for early detection of type 2 diabetes mellitus (T2DM) is challenged by its asympto...

Dec 2024 http://arxiv.org/abs/2412.10955v1

Predicting Emergency Department Visits for Patients with Type II Diabetes

Over 30 million Americans are affected by Type II diabetes (T2D), a treatable condition with signi...

Dec 2024 http://arxiv.org/abs/2412.08984v1

Derivative-Based Mir Spectroscopy for Blood Glucose Estimation Using Pca-Driven Regression Models

In this study, we presented two innovative methods, which are Threshold-Based Derivative (TBD) and...

Dec 2024 http://arxiv.org/abs/2412.07821v1

Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.

This research aims to enhance our comprehensive understanding of the influence of type-2 diabetes on...

Dec 2024 39654201

Multi-Omics Integration With Machine Learning Identified Early Diabetic Retinopathy, Diabetic Macula Edema and Anti-VEGF Treatment Response.

PURPOSE: Identify optimal metabolic features and pathways across diabetic retinopathy (DR) stages, d...

Dec 2024 39671223

Endocrinology

Browse Categories

Machine learning-based coronary heart disease diagnosis model for type 2 diabetes patients.

SMART (artificial intelligence enabled) DROP (diabetic retinopathy outcomes and pathways): Study protocol for diabetic retinopathy management.

Using Machine Learning and Artificial Intelligence to Predict Diabetes Mellitus among Women Population.

Machine Learning and Augmented Intelligence Enables Prognosis of Type 2 Diabetes Prior to Clinical Manifestation.

Continuous glucose monitoring using machine learning models and IoT device data: A meta-analysis.

SwinDFU-Net: Deep learning transformer network for infection identification in diabetic foot ulcer.

Enhancing Transfer Learning for Medical Image Classification with SMOTE: A Comparative Study

A Comparative Study on Machine Learning Models to Classify Diseases Based on Patient Behaviour and Habits

Homogenization of Ordinary Differential Equations for the Fast Prediction of Diabetes Progression

Risk prediction of integrated traditional Chinese and western medicine for diabetes retinopathy based on optimized gradient boosting classifier model.

Advances in Artificial Intelligence forDiabetes Prediction: Insights from a Systematic Literature Review

Deep Learning-Based Noninvasive Screening of Type 2 Diabetes with Chest X-ray Images and Electronic Health Records

Predicting Emergency Department Visits for Patients with Type II Diabetes

Derivative-Based Mir Spectroscopy for Blood Glucose Estimation Using Pca-Driven Regression Models

Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.

Electronic Health Records-Based Data-Driven Diabetes Knowledge Unveiling and Risk Prognosis

DiffuPT: Class Imbalance Mitigation for Glaucoma Detection via Diffusion Based Generation and Model Pretraining

Diabetic Retinopathy Classification from Retinal Images using Machine Learning Approaches

Exploring Long-Term Prediction of Type 2 Diabetes Microvascular Complications

Domain Adaptive Diabetic Retinopathy Grading with Model Absence and Flowing Data

Multi-Omics Integration With Machine Learning Identified Early Diabetic Retinopathy, Diabetic Macula Edema and Anti-VEGF Treatment Response.

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