Endocrinology

Malignant Transformation Risk in Patients With Oral Leukoplakia and Type 2 Diabetes Mellitus.

INTRODUCTION AND AIMS: Oral leukoplakia (OLK) is the most common oral potentially malignant disorder, with a malignant transformation rate of up to 9.8%. Type 2 diabetes mellitus (T2DM) is associated with increasing cancer risk. However, risk factors for malignant transformation in OLK-T2DM patients remain undefined. This study aimed to identify these factors and develop prediction models integrat...

Improving Long-Term Adherence to Endocrine Therapy Among Breast Cancer Survivors: Development of a Multiscale Modeling and Intervention System.

BACKGROUND: Breast cancer is a significant public health burden. Despite its critical role in preventing the recurrence of breast cancer, rates of long-term adherence to endocrine therapy (ET) remain low among certain breast cancer survivors. Using embedded sensors in smartphones and wearables, ecological momentary assessment data and health behavior theory may facilitate a richer understanding of...

Genetic association and machine learning improve the prediction of type 1 diabetes risk.

Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can enhance biological and therapeutic discovery and improve ...

Unsupervised clustering analysis reveals distinct postoperative cortisol trajectories following pituitary adenoma resection in Cushing's disease.

The evolving role of artificial intelligence in optimizing treatment and patient selection in diabetic macular edema.

Anti-vascular endothelial growth factor (anti-VEGF) therapy is the mainstay of management for diabetic macular edema (DME), but marked variability in ...

[Artificial intelligence-assisted diagnostics in the pathology of internal and oncological diseases].

BACKGROUND: Artificial intelligence (AI) is increasingly being implemented in digital pathology to support the tissue classification, cell detection, ...

Using machine learning to identify the most important predictors of fatty liver index in healthy young Taiwanese men.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide. While many factors have been associated with NAFLD, their...

An advanced hybrid deep learning framework for high-precision brain tumor detection and classification in MRI scans.

Early and accurate identification of brain tumors from magnetic resonance imaging (MRI) is essential for timely clinical intervention; however, manual...

Diagnosis of Acromegaly.

The clinical presentation of acromegaly reflects systemic effects of chronic GH and IGF-I excess. Diagnostic delay frequently ranges from 6 to 10 year...

A lightweight GhostYOLO framework with GhostDynamic Module and multi-scale attention for thyroid nodule diagnosis.

Ultrasound is the primary tool for thyroid nodule assessment, but diagnostic accuracy and efficiency require improvement. This study aims to develop a...

Precision Medicine in Autoimmune Thyroid Diseases: Decoding Biomarkers, Targeted Therapies and Digital Innovation.

INTRODUCTION: Autoimmune thyroid diseases (AITDs), including Graves' disease and Hashimoto's thyroiditis, arise from genetic, epigenetic, and environm...

Smart nanomaterials enabling drug delivery and glucose monitoring for diabetes management.

Diabetes mellitus represents one of the most prevalent chronic diseases worldwide, posing serious challenges to global health and healthcare sustainab...

Development of a risk prediction model for second primary thyroid cancer in female breast cancer patients based on machine learning algorithms.

Female breast cancer patients remain at risk of developing additional primary cancers even following surgical treatment. Second primary thyroid cancer...

Trajectory excited-state dynamics study of pyrazine: Assessment of potential energy surfaces and simulation of picosecond timescales.

The femtosecond and picosecond excited-state dynamics of pyrazine are studied using full-dimensional trajectory surface hopping (TSH) dynamics simulat...

Machine Learning Unveils Dietary Antioxidants as Influential Factors for Diabetes-Cancer Comorbidity: Insights From National Health and Nutrition Examination Survey.

This study aims to assess the predictive value of dietary antioxidants in diabetes-cancer comorbidity using interpretable machine learning (ML) models...

Selective and Sustainable Recovery of High-Value Metals from e-Waste via a Glucose-Mediated Hydrothermal Process.

The rapid fabrication of artificial intelligence-based hardware worldwide is intensifying the electronic waste (e-waste) crisis, threatening ecosystem...

Integrative gene ontology-driven analysis of the eutopic endometrium reveals key dysregulated functionomes and pathways in endometriosis.

BACKGROUND: Endometriosis is a chronic estrogen-dependent inflammatory disorder associated with pelvic pain, infertility, and an increased risk of end...

Artificial Intelligence-Enabled Analysis of Radiology Reports: Epidemiology and Outcomes of Incidental Thyroid Findings.

CONTEXT: Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, an...

A decade of evidence linking gut microbiome dysbiosis to depression: a computational meta-analysis of mechanistic pathways: 2014-2024.

OBJECTIVES: The gut microbiome-gut-brain axis (MGBA) has been associated in the pathophysiology of depression; however, the expanding literature remai...

Integration of Continuous Glucose Monitoring With HbA1c to Improve the Detection of Prediabetes in Asian Individuals: Model Development Study.

BACKGROUND: Glycated hemoglobin (HbA1c) is a convenient tool to evaluate glycemic status but its ability to detect individuals at risk for type 2 diab...