Urology

Cancer burden and health inequalities attributable to occupational arsenic exposure: A 32-year global, regional, and national observational study with projections to 2036.

Occupational arsenic exposure (OEA), mainly through inhalation in workplace settings, is an established carcinogenic hazard associated with lung, skin, and bladder cancers. However, long-term trends and the global cancer burden attributable to OEA remain insufficiently characterized. Data from the Global Burden of Disease Study 2021 were used to analyze the cancer burden attributable to OEA from 1...

[Use of artificial intelligence in clinical practice and hospitals].

Artificial intelligence (AI) is increasingly evolving from a research technology into a tool for everyday clinical practice. While early applications primarily focused on medical image analysis, generative AI systems and large language models are now available for a wide range of clinical and administrative tasks. These include medical documentation, literature review, guideline-based knowledge ma...

Predictors of atrial fibrillation recurrence after catheter ablation: a systematic review.

BACKGROUND: Recurrence of atrial fibrillation (AF) following catheter ablation is a major clinical problem, and there is considerable variability in p...

Era-specific prognostic factors and an interpretable machine-learning survival model for renal cell carcinoma brain metastases.

BACKGROUND: Brain metastases (BM) in renal cell carcinoma (RCC) are associated with poor prognosis and limited clinical guidance. We aimed to identify...

Screening foundational machine learning models using the adsorption of thiophene on transition metal surfaces.

This article presents a computational screening of several popular foundational machine learning models on the adsorption of thiophene, C4H4S, on Ir, ...

Cardiovascular risks of plastic-associated chemicals: Integrating mixture modeling and SHAP-explained machine learning to unravel linear and non-linear associations.

INTRODUCTION: Plastic-associated chemicals (PACs) are widely detected environmental contaminants, yet their cardiovascular relevance in the context of...

From Uniformity to Individuality: Computational Modelling Provides a Mechanistic Rationale for Weight-Adjusted Botulinum Neurotoxin A Dosing.

Fixed-dose Botulinum neurotoxin type A regimens ignore patient-specific variables, such as body weight, despite allometric principles governing the di...

Real World Evaluation of AI-Based Tumor Cell Content Quantification for Molecular Tumor Profiling.

PURPOSE: Repeated evidence demonstrates limited reproducibility and accuracy of the visual quantification (VQ) of the tumor cell content (TCC) by clin...

Predictive biomarkers for immunotherapy response in renal cell carcinoma: why have they failed?

PURPOSE OF REVIEW: The heterogeneity of response to immunotherapies in renal cell carcinoma has created a strong need for predictive biomarkers to gui...

The promise of deep urine proteomics for diagnosis of cancer, neurologic, and metabolic diseases.

INTRODUCTION: Urine offers a noninvasive and low-cost source of disease biomarkers, yet most proteomic studies have targeted single conditions. Using ...

Prediction of postoperative acute kidney injury in patients undergoing off-pump coronary artery bypass grafting: A machine learning model.

BACKGROUND: The incidence of cardiac surgery-associated acute kidney injury (CSA-AKI) is 26.0%-28.5%. Among cardiac procedures, off-pump coronary arte...

[Artificial intelligence in the care of geriatric patients-more of a curse or more of a blessing?].

BACKGROUND: Artificial intelligence (AI) is conquering medicine in many fields. With geriatric patients, it is important not only to understand the de...

The use of artificial intelligence to predict postoperative outcomes following percutaneous nephrolithotomy: A systematic review of prognostic modeling studies.

Artificial intelligence (AI) is increasingly applied in clinical practice to enhance prediction of postoperative outcomes. This systematic review eval...

Performance of 5 Large Language Models in Perioperative Consultation for Pediatric Hypospadias: Cross-Sectional Comparative Study.

BACKGROUND: Hypospadias is a common congenital malformation requiring surgery. Caregivers face substantial perioperative information needs, and large ...

Development and validation of an integrated machine learning model for recurrence-free survival prediction in clear cell renal cell carcinoma.

BACKGROUND: Integrated multimodal systems improve recurrence-free survival (RFS) prediction in surgically resected clear cell renal cell carcinoma (cc...

Identification of key biomarkers for ferroptosis in diabetic kidney disease using machine learning and WGCNA.

OBJECTIVE: Early detection of diabetic kidney disease (DKD) remains challenging because currently available clinical markers mainly reflect establishe...

RenalTox-XAI: Applicability-Domain-Constrained and Descriptor-Guided QSAR Framework for Early Screening and Safety Prioritization of Drug-Induced Renal Injury.

Drug-induced renal injury (DIRI) remains a major cause of drug attrition and post-marketing safety concerns, highlighting the need for reliable early-...

Deep learning-based multi-modality image conversion for evaluating dose calculation and position correction accuracy in image-guided radiation therapy.

Cone-beam CT (CBCT) is widely used in image-guided radiation therapy (IGRT). However, CBCT has limited image quality, which can reduce dose calculatio...

Identification of Methionine Metabolism-Driven Heterogeneous Subtypes in Colorectal Cancer and Their Associated Immune Microenvironment.

AIM: Tumor heterogeneity, driven by metabolic reprogramming, challenges colorectal cancer (CRC) treatment. Methionine metabolism is crucial for tumor ...

Targeted radionuclide-drug conjugates: Current status and perspectives.

Radionuclide drug conjugates (RDCs) are emerging molecular platforms for diagnostic imaging, targeted radionuclide therapy, and precision-oncology the...