Endocrinology

Exploring the prognostic impact of triglyceride-glucose index in critically ill patients with first-ever stroke: insights from traditional methods and machine learning-based mortality prediction.

BACKGROUND: The incidence and mortality of first-ever strokes have risen sharply, especially in the intensive care unit (ICU). Emerging surrogate for insulin resistance, triglyceride-glucose index (TyG), has been linked to stroke prognosis. We aims to explore the relationships between TyG with ICU all-cause mortality and other prognosis, and to develop machine learning (ML) models in predicting IC...

A prior-knowledge-guided dynamic attention mechanism to predict nocturnal hypoglycemic events in type 1 diabetes.

Nocturnal hypoglycemia is a critical problem faced by diabetic patients. Failure to intervene in time can be dangerous for patients. The existing early warning methods struggle to extract crucial information comprehensively from complex multi-source heterogeneous data. In this paper, a deep learning framework with an innovative dynamic attention mechanism is proposed to predict nocturnal hypoglyce...

Standardized evaluation of diabetic retinopathy using artificial intelligence and its association with metabolic dysfunction-associated steatotic liver disease in Japan: A cross-sectional study.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is common in patients with obesity and diabetes and can lead to serious complications...

Clinical characteristics of adrenal crisis in 371 adult patients with glucocorticoid-induced adrenal insufficiency.

BACKGROUND: Glucocorticoid-induced adrenal insufficiency (GIAI) is a hypothalamic-pituitary-adrenal (HPA) axis dysfunction caused by long-term use of ...

Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases.

Thyroid diseases, including functional and neoplastic diseases, bring a huge burden to people's health. Therefore, a timely and accurate diagnosis is ...

L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction.

Pre-training strategies based on self-supervised learning (SSL) have demonstrated success as pretext tasks for downstream tasks in computer vision. Ho...

Potential shared mechanisms in atopic dermatitis and type 2 diabetes identified via transcriptomic and machine learning approaches.

Although atopic dermatitis (AD) and type 2 diabetes mellitus (T2DM) may appear clinically and pathophysiologically unrelated, AD is a common skin dise...

Serum PD-1 regulation and PD-1 expression of CD4+Foxp3+ regulatory T cells in patients in thyroid eye disease associated with immunosuppression treatment.

PURPOSE: Thyroid eye disease (TED) primarily occurs in hyperthyroid patients, sometimes resulting in poor visual prognosis. Although other autoimmune ...

Endocrine disruptor identification and multitoxicity level assessment of organic chemicals: An example of multiple machine learning models.

Endocrine-disrupting chemicals (EDCs) pollution is a major global environmental issue. Assessing the multiple toxic effects of EDCs is key to managing...

XGBoost-based nomogram for predicting lymph node metastasis in endometrial carcinoma.

This study aims to construct and optimize risk prediction models for lymph node metastasis (LNM) in endometrial carcinoma (EC) patients, thus improvin...

Effects of melatonin on the mitogen-activated protein kinase signaling genes in hypoxic Leydig cells.

Leydig cells play a crucial role in male reproductive physiology, and their dysfunction is often associated with male infertility. Hypoxia negatively ...

Advances in Machine Learning-Aided Thermal Imaging for Early Detection of Diabetic Foot Ulcers: A Review.

The prevention and early warning of foot ulcers are crucial in diabetic care; however, early microvascular lesions are difficult to detect and often d...

Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management.

One of the health challenges in the 21st century is to rethink approaches to non-communicable disease prevention. A solution is a smart city that impl...

Identification and verification of the optimal feature genes of ferroptosis in thyroid-associated orbitopathy.

BACKGROUND: Thyroid-associated orbitopathy (TAO) is an autoimmune inflammatory disorder of the orbital adipose tissue, primarily causing oxidative str...

A clinical practical model for preoperative prediction of visual outcome for pituitary adenoma patients in a retrospective and prospective study.

OBJECTIVE: Preoperative prediction of visual recovery after pituitary adenoma resection surgery remains challenging. This study aimed to investigate t...

Comparative study of alpha-glucosidase inhibition of four Vietnamese medicinal plants , , , and : and studies.

Four medicinal plants , , , and growing in the South of Vietnam were investigated for their alpha-glucosidase inhibition. The crude methanol extract ...

Exploring diabetes through the lens of AI and computer vision: Methods and future prospects.

Early diagnosis and timely initiation of treatment plans for diabetes are crucial for ensuring individuals' well-being. Emerging technologies like art...

Genotype-negative multiple endocrine neoplasia type 1 with prolactinoma, hyperparathyroidism, and subclinical Cushing's syndrome accompanied by hyperglycemia: a case report.

BACKGROUND: Multiple endocrine neoplasia type 1 (MEN1) is a rare autosomal dominant disorder, accompanied by multiple endocrine neoplasms of the parat...

The native Iranian soil bacteria with high potential to produce extracellular methionine gamma-lyase.

This study aimed to screen native methionine gamma-lyase (L-methioninase) producing bacteria from soil samples and optimize the culture media for enha...

Early Detection of Dementia in Populations With Type 2 Diabetes: Predictive Analytics Using Machine Learning Approach.

BACKGROUND: The possible association between diabetes mellitus and dementia has raised concerns, given the observed coincidental occurrences.