Urology

Impact of an Artificial Intelligence-Powered Clinical Decision Support System for Acute Kidney Injury Prevention in the Intensive Care Unit: Single-Center Uncontrolled Before-and-After Implementation Study.

BACKGROUND: Acute kidney injury (AKI) is a frequent and serious complication among hospitalized patients, particularly in critical care settings, where its incidence can exceed 50%. AKI is associated with increased mortality, prolonged hospitalization, dialysis dependence, and higher health care costs. Although the KDIGO (Kidney Disease: Improving Global Outcomes) guidelines emphasize supportive c...

Aptamer-Directed Assembly of NSET Microneedle Patch for Early Detection of Acute Kidney Injury Facilitated by Deep Learning-Enabled Target Signal Extraction.

Neutrophil gelatinase-associated lipocalin (NGAL) is a promising early biomarker for acute kidney injury (AKI), yet current biosensors lack the capability for minimally invasive, in situ, real-time analysis of interstitial fluid (ISF)-a key medium suitable for reliable continuous monitoring. Herein, we propose an aptamer-directed assembly strategy for the preparation of a nanocomposite microneedle...

MRI-Only Simulation for Prostate MRI-Guided SBRT.

PURPOSE: The SMART (Stereotactic MR-Guided Adaptive Radiation Therapy) protocol for prostate SBRT has demonstrated favorable clinical outcomes using a...

Biological aging and the incidence and progression of diabetic retinopathy and kidney disease in type 2 diabetes mellitus: A prospective cohort study.

AIMS: We examined whether phenotypic age (PhenoAge) acceleration was associated with the incidence and progression of diabetic retinopathy (DR) and di...

Automated body composition quantification from non-contrast CT for urolithiasis classification and exploratory incident risk assessment.

To develop a deep learning-based body composition quantification framework from non-contrast CT for urolithiasis classification (calcium, non-calcium,...

Anatomically Localized Detection of Six Acute Abdominal Emergencies on CT Using Multi-window Deep Learning: Development and Validation.

The purpose of this study is to develop and retrospectively validate a deep learning system for the classification and anatomically interpretable loca...

Identification of the oxidation stress-related gene signatures and functional verification of MINK1 in prostate cancer cells.

BACKGROUND: A major challenge facing prostate cancer (PCa) cells is oxidative stress, yet the precise role and underlying mechanisms remain inadequate...

Multimodal imaging to analyze the biomechanical properties of kidney tumors, evaluating feasibility, inter-modality correspondence, and diagnostic value (UroCCR-115).

INTRODUCTION: Assessment of renal tissue and renal tumor stiffness may provide complementary information for tissue characterization; however, convent...

Identification and verification of immunogenic cell death-related signatures derived from bone metastasis of prostate cancer based on multi-omics and machine learning algorithms.

BACKGROUND: Prostate cancer (PCa) is a prevalent urological malignancy in men, with bone metastasis occurring in the majority of patients, often leadi...

Association of C-reactive protein to albumin ratio with progression of CKD and all-cause mortality in diabetic CKD.

INTRODUCTION: The C-reactive protein to albumin ratio (CAR), an integrative biomarker of inflammation and malnutrition, has shown prognostic value in ...

Magnetic Resonance Imaging-Based Artificial Intelligence in Predicting Prostate Cancer Biochemical Recurrence: Systematic Review and Meta-Analysis.

BACKGROUND: Artificial intelligence (AI) has emerged as a promising tool for prostate cancer (PCa) risk stratification and outcome prediction. However...

Bisphenol a exposure induces low back pain associated with intervertebral disc degeneration via BIRC3-mediated nucleus pulposus cell senescence.

OBJECTIVE: This study aimed to assess the correlation of bisphenol A (BPA) exposure with low back pain (LBP) and determine if the underlying molecular...

A Predictive Nomogram Integrating AI-Assisted Morphological Feature Extraction with Clinical and Ultrasound Parameters for Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer.

OBJECTIVE: To develop and validate a nomogram integrating artificial intelligence (AI)-extracted ultrasound features with clinic pathologic data for n...

ProCDNet: prostate cancer detection network using quantum machine learning with enhanced addax optimization.

Prostate cancer is one of the most prevalent malignancies worldwide, necessitating the development of advanced and efficient detection models. This re...

Domain Generalization Mitigates Scanner-Induced Domain Shift in Medical Imaging.

Deep learning models for medical image analysis often fail in clinical deployment due to domain shift from varied acquisition hardware and protocols. ...

Heatstroke Over the Past Decade: Risk Factors, Long-Term Health Consequences, and Preventive Measures.

BACKGROUND: Heatstroke (HS) encompasses acute multi-organ dysfunction and increases susceptibility to subsequent heat-related conditions, making timel...

The doctors of the future: the competition of ChatGPT-4, ChatGPT-4 omni, and Gemini 2.0 Flash in andrology.

OBJECTIVES: Large language models (LLMs) are increasingly being used in medical research and as clinical decision-support tools. This study aimed to c...

Development of multiphasic CT-based delta-radiomics model for predicting postoperative recurrence risk in bladder cancer.

BACKGROUND: This study aimed to develop a CT-based delta-radiomics model for personalized prediction of postoperative prognosis in bladder cancer pati...

An AI-powered diagnostic system for grading and invasion of non-muscle-invasive bladder cancer via TURBT specimens: A multicenter study.

Early pathological examination for grading and invasion of non-muscle-invasive bladder cancer (NMIBC) via transurethral resection of bladder tumor (TU...

Detection of hypodense hepatic and renal lesions on abdominal CT reconstructed with deep learning image reconstruction technique in patients with large body habitus: A multi-reader study.

PURPOSE: To evaluate detectability of hypodense hepatic and renal lesions on portal venous phase CT reconstructed with deep learning image reconstruct...