Menopause

Beyond target lesions: Prognostic value of longitudinal AI-derived whole-body [1⁸F]FDG PET/CT metrics in metastatic melanoma.

PURPOSE: To investigate the prognostic value of an artificial intelligence (AI)-based semi-automated tool for longitudinal whole-body quantification of total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) on [1⁸F]FDG PET/CT in patients with metastatic melanoma undergoing immune checkpoint inhibitor (ICI) therapy, and to assess its prognostic relevance alongside established PET-bas...

Machine learning-driven evaluation of mechanical and microstructural properties of agro-waste-derived geopolymer concrete.

The growing demand for sustainable construction materials has accelerated research into eco-friendly alternatives to traditional Portland cement. This research explores the potential of geopolymer concrete formulated from agricultural-waste ashes as a sustainable replacement for conventional Portland cement. Banana peel ash (BPA) and sugarcane bagasse ash (SCBA) were employed as aluminosilicate pr...

Comment on "integrating machine learning into fracture liaison services: Toward precision risk stratification in osteoporosis care".

Exploring osteoporosis risk in breast cancer patients after comprehensive treatment via explainable artificial intelligence algorithms.

BACKGROUND: Osteoporosis is a common complication among long-term breast cancer (BC) survivors. Assessment of osteoporosis risk of patients before the...

Leveraging the non-contrast CT component of PET/CT: an AI-driven delta-radiomics approach to monitor treatment response in metastatic breast cancer.

PURPOSE: 18 F-FDG PET/CT is the standard modality for monitoring treatment response in metastatic breast cancer. This study aims to evaluate the predi...

Explainable machine learning-guided integrated multiomics analysis reveals macrophage-driven immune suppression in breast cancer.

Despite thorough characterizations of cellular compositions within the breast tumor microenvironment (TME), their implications for disease progression...

Uncovering subgroup heterogeneity in dyslexia intervention outcomes using explainable machine learning.

Identifying heterogeneity within literacy intervention outcomes can inform more targeted strategies for dyslexia remediation. Based on prior work that...

Hallmarks of epithelial-mesenchymal plasticity in cancer.

Cancer stem cells (CSCs) drive tumour initiation, progression, metastasis, and therapy resistance through their remarkable plasticity, enabling dynami...

MicroRNAs in endometriosis: bioinformatics resources, machine learning strategies, and multi-omics perspectives.

BACKGROUND: Endometriosis is a heterogeneous gynecological disorder characterized by chronic pain, infertility, and substantial impairment of quality ...

Mean airway pressure as an independent risk factor for developing acute kidney injury in mechanically ventilated critically ill patients: a multi-center retrospective analysis.

Mechanical ventilation is a well-recognized risk factor for acute kidney injury (AKI), but the specific role of mean airway pressure (Pmean) remains i...

Targeting dysregulated glycolysis in type 2 diabetic osteoporosis: Identification of a diagnostic gene signature and therapeutic validation of calcifediol.

Type 2 diabetic osteoporosis (T2DOP) is a significant complication of type 2 diabetes, characterized by an increased risk of fractures. While dysregul...

Treatment effect heterogeneity of radiotherapy in localized Ewing sarcoma: A secondary analysis of the EURO-E.W.I.N.G. 99 and Ewing 2008 trial.

INTRODUCTION: Standard Ewing sarcoma treatment includes chemotherapy and local therapy. Previous studies found no average treatment effect of combined...

The progesterone to estradiol ratio predicts fear extinction in mice and humans.

Sex differences in fear memory are well documented, yet the role of menstrual cycle phases and ovarian hormone dynamics remains unclear. Here, we inve...

Spliceread: improving canonical and non-canonical splice site prediction with residual blocks and synthetic data augmentation.

Accurate splice site prediction is fundamental to understanding gene expression and its associated disorders. However, most existing models are biased...

Mechanisms linking primary biliary cholangitis and osteoporosis: A combined clinical and molecular analysis.

Primary biliary cholangitis (PBC) is an immune-mediated cholestatic liver disease, and osteoporosis (OP) is a prevalent comorbidity that aggravates th...

Real‑World Clinical Characterization of Major Depressive Disorder and Treatment‑Resistant Depression Supported by Natural Language Processing: Multicenter Observational Study From the MOOD Project.

BACKGROUND: Major depressive disorder (MDD) and treatment-resistant depression (TRD) are heterogeneous conditions in which key clinical details are sp...

Performance of Large Language Models in Answering Osteoporosis-Related Frequently Asked Questions: A Systematic Comparative Evaluation Based on International Associations.

To systematically evaluate and compare the performance of large language models (LLMs) in answering osteoporosis-related frequently asked questions (F...

Radiomics analysis of restaging MRI for detection of pathological complete response in locally advanced rectal cancer.

PURPOSE: magnetic resonance imaging (MRI)-based radiomics has emerged as a promising approach for non-invasive prediction of treatment response in rec...

Machine Learning Prediction of Growth Hormone Response in Children Non-Growth Hormone-Deficient Short Stature.

Height gain under recombinant human growth hormone (rhGH) varies widely in children with short stature, making early, reliable response prediction ess...

Hyperbaric oxygen in the artificial intelligence era: integration and innovation.

Hyperbaric oxygen therapy is established for decompression illness, carbon monoxide poisoning, radiation-induced tissue injury, and diabetic foot ulce...