Endocrinology

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

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Diabetes knowledge in young adults: associations with hemoglobin A1C.

The purpose of this study was to quantify associations between hemoglobin A1C (A1C) and diabetes kno...

Noninvasive blood glucose sensing using near infra-red spectroscopy and artificial neural networks based on inverse delayed function model of neuron.

In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) sp...

The Impact of Oversampling with SMOTE on the Performance of 3 Classifiers in Prediction of Type 2 Diabetes.

OBJECTIVE: To evaluate the impact of the synthetic minority oversampling technique (SMOTE) on the pe...

European Association of Endoscopic Surgeons (EAES) consensus statement on the use of robotics in general surgery.

Following an extensive literature search and a consensus conference with subject matter experts the ...

Hypoglycemia prediction using machine learning models for patients with type 2 diabetes.

Minimizing the occurrence of hypoglycemia in patients with type 2 diabetes is a challenging task sin...

Rule extraction from support vector machines using ensemble learning approach: an application for diagnosis of diabetes.

Diabetes mellitus is a chronic disease and a worldwide public health challenge. It has been shown th...

Creating a place for caregivers in personal health: the iHealthSpace copilot program and diabetes care.

BACKGROUND: As America's baby boom generation reaches retirement, the number of elders, and, in turn...

The accuracy of Machine learning in the prediction and diagnosis of diabetic kidney Disease: A systematic review and Meta-Analysis.

PURPOSE: Machine learning (ML) has gained attention in diabetes management, particularly for predict...

A scoping review of digital solutions in diabetes outpatient care: Functionalities and outcomes.

BACKGROUND: Digital interventions are increasingly used in outpatient diabetes care to address growi...

Evaluation of insulin sensitivity temporal prediction by using quantile regression combined with neural network model.

BACKGROUND: Stress-induced hyperglycemia, a pathologically high blood glucose level, is a frequent c...

Decoding chronic stress: From behavioral-molecular dynamics in mice to clinical implications of cortisol and IL-17 in depression severity.

BACKGROUNDS: The etiology of depression involves chronic stress, a recognized determinant of onset a...

A comparative analysis of deep learning architectures for thyroid tissue classification with hyperspectral imaging.

Hyperspectral imaging has shown significant applicability in the medical field, particularly for its...

Supervised model based polycystic ovarian syndrome detection in relation to vitamin d deficiency by exploring different feature selection techniques.

Due to urbanization and modern lifestyle, most of women in today's world are prone to Polycystic Ova...

Optimized deep learning for brain tumor detection: a hybrid approach with attention mechanisms and clinical explainability.

Brain tumor classification (BTC) from Magnetic Resonance Imaging (MRI) is a critical diagnosis task,...

Hub biomarkers and their clinical relevance in glycometabolic disorders: A comprehensive bioinformatics and machine learning approach.

BACKGROUND: Gluconeogenesis is a critical metabolic pathway for maintaining glucose homeostasis, and...

Integration of multi-omics data and machine learning to identify antioxidant biomarkers in type 1 diabetes.

The identification of biomarkers for early diagnosis and monitoring the progression of Type 1 Diabet...

Predicting estrogen receptor agonists from plastic additives across various aquatic-related species using machine learning and AlphaFold2.

The absence of effective public databases greatly limits high-throughput prediction of hormonal effe...

Early Identification of Vitamin D Deficiency Risk Through Public Health Screening Data.

Metabolic syndrome, characterized by central obesity, hypertension, hyperglycemia, dyslipidemia, and...

ICU Length of Stay Prediction for Patients with Diabetes Using Machine Learning and Clinical Notes.

Diabetes, a chronic disease, often leads to poor health outcomes and increased healthcare costs, par...

Exploring Machine Learning for Predicting Peripheral and Central Precocious Puberty Through Cross-Hospital Validation.

Precocious puberty, including Peripheral Precocious Puberty (PPP) and Central Precocious Puberty (CP...

Enhancing Chronic Diabetes Care with Companion Robots in Rural Taiwan.

Managing chronic diabetes in rural Taiwan remains challenging due to limited medical access and low ...

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