Menopause

Imaging foundation model for universal enhancement of non-ideal measurement CT.

Non-ideal measurement computed tomography (CT) employs suboptimal imaging protocols to expand CT applications. However, the resulting trade-offs degrade image quality, limiting clinical acceptability. Although deep learning methods have been used to enhance non-ideal measurement CT images, their reliance on large training datasets and limited generalizability across diverse settings hinder practic...

Machine learning-driven prediction of mechanical properties of lightweight concrete based on experimental data.

Lightweight concrete (LWC) is increasingly used in structural and non-structural applications due to its ability to reduce self-weight while maintaining adequate mechanical performance. However, predicting the mechanical behavior of EPS-based lightweight concrete remains challenging because of the complex and nonlinear interactions between mix composition, density, curing age, and aggregate-matrix...

ABCA8 drives bone loss via disrupting Th17/Treg imbalance: a novel immunometabolic target for osteoporosis.

BACKGROUND: Osteoporosis is a metabolic bone disease characterized by reduced bone mass and microarchitectural deterioration, with complex involvement...

An explainable machine learning approach to predict fragility fractures and the identification of important features.

In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence of fractures at different skeletal sites, using t...

Human expertise or artificial intelligence? A prospective study on nail disorder diagnosis.

Artificial intelligence (AI) shows promise in analyzing patterns of nail disease. This prospective, comparative study compared the diagnostic performa...

Integrating network toxicology, machine learning, and single-cell sequencing to reveal the FASN-mediated role of phenolic endocrine disruptors in water in promoting prostate cancer.

BACKGROUND: Phenolic endocrine-disrupting chemicals (EDCs) like nonylphenol (NP) and octylphenol (OP) are widespread water pollutants. Their estrogen-...

Construction of liver organoid models by hepatobiliary differentiation from human induced pluripotent stem cells: state of the art, challenges and improving strategies.

Physiologically relevant liver models are essential for advancing hepatic disorder research, especially for disease modeling and drug development, yet...

Performance comparison of a neuro-symbolic large language model system versus conventional AI models and human experts in cholangitis management.

BACKGROUND: Large language models (LLMs) have shown promising results in medical decision support; Background: Large language models (LLMs) have demon...

Fractal analysis in dentistry: a bibliometric analysis (1991-2024).

OBJECTIVES: This study aims to provide a comprehensive bibliometric mapping of the scientific evolution and research trends of fractal analysis (FA) i...

Nanostructured electrode materials and flexible-substrate engineering for wearable multi-analyte biosensors in diabetes monitoring and personalized care: a comprehensive review.

This review examines the convergence of wearable biosensors and artificial intelligence (AI) in personalized diabetes care. It addresses the limitatio...

Environmental Levels of Sodium p-Perfluorous Nonenoxybenzene Sulfonate Induce Nephritis in Renal Proximal Tubular Epithelial Cells via Modulation of Estrogen Signaling Pathways.

Sodium p-perfluorous nonenoxybenzene sulfonate (OBS), widely used as an alternative to per- and polyfluoroalkyl substances, has been implicated in tox...

Explainable artificial intelligence in prostate cancer treatment recommendation: A decision support system for oncological expert panels.

BACKGROUND: Therapeutic decisions in clinical oncology are commonly established through interdisciplinary consensus in multidisciplinary cancer confer...

Guideline Adherence in the Diagnosis of PCOS Among Adolescents: Comparing Obstetricians and Gynecologists With Large Language Models.

STUDY OBJECTIVE: Polycystic ovary syndrome in adolescence is a condition associated with long-term cardiovascular, metabolic, and psychological outcom...

Prevalence and Predictors of Non-Exclusive Breastfeeding at Hospital Discharge in Uruguay.

BACKGROUND: The prescription of infant formula during postpartum hospitalization is one of several factors that influence breastfeeding. RESEARCH AIMS...

Exosomes in bone health and disease: cellular crosstalk, systemic signaling, and AI-driven advances in regenerative therapy.

Exosomes have emerged as critical mediators of intercellular and inter-organ communication in bone biology. Secreted by bone-resident cells such as os...

Machine learning identifies traffic-related pollutant mixtures as potential factors suggestive of association with osteoporosis in a cross-sectional analysis of NHANES.

The combined effect of traffic-related pollutant mixtures on osteoporosis (OP) remains unclear. This study aimed to evaluate such associations using m...

Integration of network pharmacology, deep learning, and molecular biology reveals the efficacy of Citrus aurantium L. var. amara Engl. blossom extract in ameliorating diabetic osteoporosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Diabetic osteoporosis (DOP) is a type of metabolic bone disease. Blossom of Citrus aurantium L. var. amara Engl. (CAVA...

Machine Learning Accelerated Non-Adiabatic Molecular Dynamics Elucidates Local Polarization Effects on Non-radiative Recombination in Halide Perovskites.

Non-radiative recombination is a critical factor limiting the optoelectronic performance of halide perovskites, yet how local polarization induced by ...

Machine learning-based prediction of hepatocellular carcinoma risk in steatotic liver disease: A nationwide cohort study.

BACKGROUND AND AIMS: Steatotic liver disease (SLD) has emerged as an important risk factor for hepatocellular carcinoma (HCC), often in the absence of...

Prediction of antibody non-specificity using protein language models and biophysical parameters.

The development of therapeutic antibodies requires optimizing target binding affinity and pharmacodynamics, while ensuring high developability potenti...