HRT

Evaluating the cost-effectiveness of artificial intelligence-enhanced osteoporosis screening in men and women using routine chest radiographs in South Korea.

South Korea, now a "super-aged" society, faces a rising burden of fragility fractures, yet underdiagnosis remains a major barrier, with limited DXA access restricting early detection. Artificial intelligence (AI) applied to routine chest radiographs enables opportunistic screening. In March 2025, Osteo Signal, a deep learning model developed in the South Korean population, received regulatory appr...

Urinary steroid metabolome shows adrenal, gonadal, and neuroactive steroid dysregulation in adolescents with depressive symptoms.

BACKGROUND: Steroid hormone profiles in affective disorders suggest hypothalamic-pituitary-adrenal (HPA) axis dysregulation and may reveal novel therapeutic targets. However, most existing studies focus narrowly on glucocorticoids. This study aims to comprehensively characterize alterations in the steroid metabolome of adolescents with depressive symptoms. METHODS: This cross-sectional study analy...

Machine learning-driven insights into the mechanical performance of polymeric microneedle array patches.

With growing interest in microneedle technology for enhancing transdermal drug delivery, the current body of literature provides a valuable data reser...

Unraveling the microbiome's role in breast cancer progression and treatment response.

The human microbiome, encompassing microbial communities in the gut and breast tissue, has emerged as a critical modulator of breast cancer (BC) initi...

Machine learning-guided composite ionic liquid-based system for dual-drug delivery targeting redox homeostasis and STAT3-PI3K axis in psoriasis therapy.

Excessive accumulation of reactive oxygen and nitrogen species (RONS) exacerbates inflammatory responses and contributes to the progression of psorias...

Development of an explainable machine learning model to reproduce and interpret expert pharmacological decisions in osteoporosis treatment.

The management of osteoporosis in real-world clinical practice is highly heterogeneous, reflecting the complexity and variability inherent in therapeu...

The New A-⊘OHO process Based on DO Gradients and Load-Ratio Allocation Enabling Mainstream PN/A in Toxic Industrial Wastewater.

The partial nitritation-anammox (PN/A) process offers significant benefits in energy conservation and carbon neutrality, however, its application is l...

Identification of common genetic features and pathways for osteoporosis with frozen shoulder by integrated bioinformatics analysis and machine learning.

Frozen shoulder (FS) and osteoporosis (OP) are common age-related degenerative diseases, occurring more frequently in females, which suggests potentia...

Integrated approaches to testing and assessment for the endocrine disrupting activity of tartrazine based on adverse outcome pathways and OECD frameworks.

Tartrazine (TTZ), a widely used synthetic azo dye in processed foods, beverages, and pharmaceuticals, raises various health concerns including hematot...

Combination of artificial intelligence and chest computed tomography to assess bone mineral density.

OBJECTIVES: To evaluate the diagnostic accuracy of artificial intelligence-assisted opportunistic chest CT for osteoporosis/osteopenia screening in a ...

Advancing osteoporosis opportunistic screening: multicenter validation of a deep learning algorithm using abdominal CT scans.

OBJECTIVES: To develop and do multicenter validation on an algorithm that screens for osteoporosis from abdominal CTs. METHODS: This is a diagnostic a...

In silico prediction of endocrine activity.

Endocrine-disrupting chemicals (EDCs) pose health risks; yet, conventional in vitro and in vivo testing remains slow, costly, and animal-intensive. En...

Artificial intelligence-driven precision treatment of reproductive medicine-related diseases: the optimal protocol choice for IVF-ET.

INTRODUCTION: Optimal ovarian stimulation (OS) selection is critical for IVF success, but expert-based decisions often lack consistency in outcomes, c...

Use of neural networks to predict a potential osteoporotic metabolic condition based on the panoramic mandibular index.

OBJECTIVE: This study investigates the use of neural networks to predict potential osteoporotic metabolic conditions using the Panoramic Mandibular In...

Evaluating bone density with ultrasonic backscatter: Leveraging time-frequency analyses and convolutional neural networks.

Osteoporosis is a disease characterized by decreased bone density and increased fracture risk. This study proposes a convolutional neural network (CNN...

AI Screening Tool Based on X-Rays Improves Early Detection of Decreased Bone Density in a Clinical Setting.

PURPOSE: Osteoporosis is an under-screened musculoskeletal disorder that results in diminished quality of life and significant burden to the healthcar...

An AI-based pipeline for osteoporosis/osteopenia prediction using hip radiographs.

OBJECTIVE: To develop and validate an artificial intelligence-based tool for the diagnosis of osteoporosis/osteopenia using hip radiographs. The tool ...

Algal/bacterial membrane bioreactor for bioremediation of hazardous landfill leachate containing 1,4-dioxane: An artificial neural network modeling.

This study developed an artificial neural network (ANN) model to predict the 1,4-dioxane removal efficiency from hazardous landfill leachate treated b...

Deep learning algorithm for identifying osteopenia/osteoporosis using cervical radiography.

Due to symptomatic gait imbalance and a high incidence of falls, patients with cervical disease-including degenerative cervical myelopathy-have a sign...

A novel dual embedding few-shot learning approach for classifying bone loss using orthopantomogram radiographic notes.

BACKGROUND: Orthopantomograms (OPGs) are essential diagnostic tools in dental and maxillofacial care, providing a panoramic view of the jaws, teeth, a...