Menopause

Evaluating an Artificial Intelligence software for opportunistic low bone mineral density and osteoporosis screening: a validation study.

Despite the profound prevalence and fracture risk of osteoporosis, access to the gold standard DXA scans remains limited, especially in rural communities. Rho is an artificial intelligence software that can identify individuals at risk of low BMD and osteoporosis using radiographs. This study will independently validate Rho software by evaluating its performance against DXA in a retrospective coho...

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 thera...

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...

Biological multi-omics approaches to next-generation biomarkers in immune-related disorders and malignancies: An overview.

Cancer and autoimmune diseases are major global health challenges characterized by molecular and clinical heterogeneity. Traditional single-analyte bi...

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...

Development and validation of a novel orthopedic blood use prediction model incorporating lab tests and thromboelastography.

OBJECTIVE: To develop and validate a prediction model integrating laboratory parameters and thromboelastography (TEG) for forecasting blood transfusio...

Early prediction of response to ADT plus ARPIs in mHSPC using interpretable machine learning on PSMA PET/CT: a real-world study.

BACKGROUND: Reliable tools for early prediction of treatment response to androgen deprivation therapy (ADT) plus novel androgen receptor pathway inhib...

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...

C-peptide Index under Non-fasting Conditions Can Predict the Likelihood of Future Insulin Therapy in Outpatients with Type 2 Diabetes Mellitus Not Receiving Insulin at Baseline.

Objective This study aimed to develop a clinical model in which the C-peptide index (CPI) under non-fasting conditions can predict future insulin ther...

Deep data consistency: A fast and robust diffusion model-based solver for inverse problems.

Diffusion models have become a successful approach for solving various image inverse problems by providing a powerful diffusion prior. Many studies ha...

Rapid MR examination with deep learning reconstruction improves diagnosis of complicated acute appendicitis.

OBJECTIVE: To evaluate the performance of a non-contrast rapid magnetic resonance imaging (MRI) protocol with deep learning reconstruction (DLR) for i...

Development and validation of a multiphase computed tomography-based radiomics classifier for differentiating retroperitoneal non-fatty dedifferentiated liposarcoma from leiomyosarcoma.

OBJECTIVE: We aimed to develop and internally validate a radiomics classification model based on multiphase computed tomography (CT) scans for preoper...

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...

Deep machine learning methods for Parkinson's disease diagnosis: a new direction in decision-making systems.

Parkinson's disease (PD) is a progressive neurodegenerative disorder primarily characterized by the gradual loss of dopamine-producing neurons in the ...

Multidimensional quantification of pain responses using novel rat pain scale reveals the absence of opioid induced hyperalgesia following chronic contingent and non-contingent morphine exposure in rats.

Opioids are often prescribed to treat chronic and post-operative pain, but there is data to suggest that opioid exposure can lead to hyperalgesia or 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...

Biased minds, sensitive hearts: Divergent neural signatures of interpersonal sensitivity in atypical and non-atypical depression.

BACKGROUND: Atypical depression (AD) is a distinct subtype of depression, with interpersonal sensitivity as one of its core characteristics. However, ...