Menopause

Perioperative prediction of adnexal malignancy by an interpretable machine learning model for guiding ovarian preservation in premenopausal endometrial cancer.

BACKGROUND: Ovarian preservation in premenopausal patients with endometrial cancer remains challenging due to the potential presence of concurrent adnexal malignancy. To support surgical decision-making, we developed an interpretable machine learning model for the perioperative identification of high-risk patients, thereby facilitating personalized ovarian preservation strategies. METHODS: We cond...

Sex Hormone Receptors, HBV Integrations and Their Prognostic Predictive Value Among Hepatocellular Carcinoma Patients.

Hepatocellular carcinoma (HCC) related to hepatitis B virus (HBV) infection predominantly affects males, yet few studies have investigated the association between sex hormones and HBV integrations, and their involvement in HCC prognosis. We assessed estrogen receptor alpha (ERα) and androgen receptor (AR) expression via immunohistochemistry on tissue microarrays constructed from 426 HBV-related HC...

Emerging trends in amino acid detection: wearable devices and machine learning-assisted signal processing.

As critical metabolic biomarkers, amino acids exert essential physiological functions, and their abnormal levels are closely associated with a range o...

Prediction of Acromial and Scapular Spine Fractures After Reverse Total Shoulder Arthroplasty using Machine Learning: A Retrospective Cohort Study.

BACKGROUND: Acromial and scapular spine fractures (ASSF) are an uncommon but significant complication following reverse total shoulder arthroplasty (r...

Body composition's effect on the bone-vascular axis of osteoporosis discovered in AI-based CT analysis of COPD patients.

OBJECTIVES: This study aimed to investigate the effect of body composition on the inverse relationship between vertebral bone density (T12 BMD) and to...

A large language model pipeline for automated citation quality scoring across engineering journal quartiles with expert validation.

This study proposes and evaluates a two-stage large language model (LLM)-based pipeline for automated citation quality scoring in academic manuscripts...

An explainable machine learning model for predicting one-year osteoporosis risk: development and validation in a prospective cohort.

OBJECTIVE: This study aimed to develop and validate an interpretable machine learning model using readily available biochemical indicators to predict ...

Unraveling the adverse outcome pathways of metabolic dysfunction-associated steatotic liver disease triggered by environmental mixtures via biological knowledge-driven machine learning.

Environmental pollutant mixtures are potential risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD), yet their joint effe...

BHOD: a bone health optimized dietary pattern designed for osteoporosis prevention.

Existing dietary patterns were not specifically designed to target osteoporosis and lack the precision required for effective prevention. We aimed to ...

Inpatient Robotic Therapy for Stroke Survivors With Severe Upper Limb Impairments: A Randomized Controlled Trial.

IMPORTANCE: Understanding how upper extremity (UE) robotic therapy (RT) affects efficiency and effectiveness of inpatient rehabilitation is important ...

Ultrasound-Based AI in Predicting Hormone Receptor Status in Breast Cancer: Is "Digital Biopsy" Possible.

Accurate and rapid determination of tumor histopathological features and molecular subtypes is critical for breast cancer prognosis and treatment stra...

Climate variability and COVID-19 non-pharmaceutical interventions shaped dengue transmission in Guangdong: an integrated modeling study.

Dengue fever is a major climate-sensitive mosquito-borne disease shaped by both environmental conditions and human behavior. We quantified the combine...

Integrated Multi-Omics Identification of Novel Diagnostic Biomarkers and Immunometabolic Therapeutic Targets in Osteoporosis via Machine Learning.

INTRODUCTION: Osteoporosis (OP) is a multifactorial skeletal disorder marked by reduced bone mass and microstructural deterioration. We investigated p...

Artificial Intelligence in medical research and publishing: progress, risks, and future perspectives.

Artificial intelligence (AI) is rapidly transforming medical research and scholarly publishing, reshaping how scientific knowledge is produced, evalua...

Artificial Intelligence for Opportunistic Screening for Osteoporosis and Spine Fractures Using Computed Tomography: A Systematic Review and Meta-Analysis.

OBJECTIVE: Osteoporosis is a major global health burden and often remains undiagnosed until fragility fractures occur. Dual-energy x-ray absorptiometr...

The future of DXA: How AI is transforming bone health diagnostics.

Dual-energy X-ray absorptiometry (DXA) remains the clinical gold standard for assessing bone mineral density (BMD), guiding diagnosis and therapeutic ...

Effects of Telerehabilitation Based on Motion Recognition Technology on Exercise Endurance of Patients With Non-Small Cell Lung Cancer After Surgery: Single-Center, Prospective, Open-Label, Randomized Controlled Trial.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for approximately 85% of primary pulmonary neoplasms. Complete surgical removal remains the co...

Deep Learning for Opportunistic Vertebral Fracture Detection on Routine Thoraco-abdominal Computed Tomography: A Systematic Review and Hierarchical Summary Receiver Operating Characteristic Meta-analysis of Patient-level Diagnostic Test Accuracy.

RATIONALE AND OBJECTIVES: Vertebral fractures (VFs) are common, clinically important, and often missed on routine chest or abdominal computed tomograp...

Myokines in exercise‑mediated bone homeostasis: Molecular signaling mechanisms and therapeutic implications for bone disorders (Review).

Skeletal muscle functions as an endocrine organ, secreting myokines that mediate interorgan communication with bone. Exercise‑induced myokines regulat...

AI-Based Pathology classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial.

PURPOSE: The ENZAMET trial established that enzalutamide added to androgen deprivation therapy (ADT) improves overall survival (OS) in metastatic horm...