Urology

AI-Assisted Prostate Cancer Diagnosis Using Biparametric MRI and PI-RADS v2.1: Performance Comparison Between Novice-Level and Experienced Readers.

BACKGROUND: Despite promising results of artificial intelligence (AI) in prostate cancer (PCa) detection, its impact on biparametric MRI (bpMRI) interpretation remains uncertain, especially for readers with limited experience. PURPOSE: To evaluate the effect of AI software assistance on prostate bpMRI interpretation by readers with different levels of prostate MRI experience. STUDY TYPE: Retrospec...

Repeatability of AI-quantified incidental findings on lung cancer screening CT scans in the NELSON trial.

OBJECTIVES: Computed tomography (CT) scans for lung cancer screening provide the opportunity of quantifying incidental findings. We evaluated the repeatability of AI-based measurements of incidental findings using short-term repeat CT scan pairs. MATERIALS AND METHODS: AI-Rad Companion Chest CT software was applied to low-dose non-contrast CT scans from the NELSON lung cancer screening trial to me...

Development and validation of a digital pathology artificial intelligence (DPAI)-derived risk score predicting Gleason grade group reclassification for patients who are candidates for active surveillance.

AIMS: Active surveillance (AS) allows selected men with localized prostate cancer to defer curative therapy and reduce treatment morbidity. Conversion...

Artificial intelligence in urology: A review of United States Food and Drug Administration-cleared devices.

OBJECTIVE: To systematically characterise United States Food and Drug Administration (FDA) authorised urology-specific artificial intelligence (AI)-en...

Navigating Uncertainty in MRI Diagnosis: A Human-AI Collaborative Strategy for Stratifying Clinically Significant Prostate Cancer.

BACKGROUND: Deep learning (DL) methods have shown potential for predicting clinically significant prostate cancer (csPCa), but radiologists often face...

Deep Learning for Ultrasound-Guided Prostate Biopsy: Toward Automated Targeting and Complication Prediction.

A preoperative Artificial Intelligence model to estimate cancer-specific mortality in nonmetastatic kidney cancer patients.

Surgical resection is the standard treatment for nonmetastatic renal cell carcinoma, yet survival outcomes vary significantly among patients. Current ...

Advances in evaluating and delivering nontechnical skills training: The use of simulation, robotics, artificial intelligence and virtual reality.

PURPOSE OF REVIEW: Nontechnical skills (NTS), such as communication, leadership, and situational awareness, are essential for ensuring surgical safety...

Augmenting clinical decision-making with large language models: evaluation across general and specialty tasks.

OBJECTIVE: Large language models (LLMs) have shown promise in clinical applications, yet prior studies mainly evaluated their standalone performance o...

Multimodal Machine Learning Integrating Clinical and Proteomic Data for Early Prediction of Hypertensive Complications: A UKB Longitudinal Study.

BACKGROUND: Hypertension is a leading risk factor for cardiovascular, cerebrovascular, and renal diseases, significantly worsening prognosis and quali...

Computed Tomography-Derived visceral fat area is associated with increased risk of kidney stone recurrence.

Visceral adiposity has been implicated in metabolic dysregulation and chronic inflammation, both of which may contribute to kidney stone recurrence. H...

Machine learning-based identification of basement membrane-related signature to predict recurrence and immunotherapy benefit in bladder cancer.

The basement membrane (BM) plays a critical role in regulating bladder cancer (BC) progression. However, a BM-related signature for predicting BC recu...

Multi-omics body-fluid biomarkers in immunoglobulin a nephropathy: Analytical Validation, standardization, and clinical chemistry translation of diagnostic and prognostic Analytes.

IgA nephropathy (IgAN) is the most prevalent primary glomerulonephritis worldwide. Although optimized supportive therapy is administered to these pati...

Network-informed multi-trait genomic analysis decodes the shared genetic architecture and therapeutic landscape of pelvic floor disorders.

Pelvic floor disorders, including pelvic organ prolapse and urinary incontinence, represent a common health burden with substantial clinical comorbidi...

Deep Learning-Based Detection of Overhanging Restorations and Calculation of Radiographic Alveolar Bone Loss Percentage with YOLOv11 and YOLOv12.

The objective of this study is to evaluate the YOLOv11 and YOLOv12 deep learning models for the detection of overhanging restorations in panoramic rad...

Longitudinal validation of ENLIGHT, an AI predictor of immunotherapy response and resistance, in pan-cancer cohorts.

Artificial intelligence (AI) algorithms such as ENLIGHT and DeepPT represent promising approaches to identify predictive biomarkers for immune checkpo...

Nationwide 30-Day Surgical Outcomes in Korea: An Interim Analysis of the Korean Quality Improvement Platform in Surgery.

BACKGROUND: National surgical registries such as the American College of Surgeons NSQIP and Japan's National Clinical Database have shown that structu...

Application Value of Radiomics-Based Machine Learning for Preoperative Risk Stratification of Bladder Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Some researchers have explored the application of radiomics-based machine learning to detect preoperative muscle invasion, high-grade tumo...

MRI-based deep learning combined with radiomics for the preoperative prediction of lymphovascular invasion in patients with bladder cancer.

BACKGROUND: Lymphovascular invasion (LVI) signifies poor prognosis in bladder cancer, yet reliable preoperative prediction remains challenging, limiti...

Comprehensive molecular analyses of a circadian rhythm-related gene diagnostic model and immune infiltration using machine learning methods in sepsis-associated acute kidney injury.

BACKGROUND: This study aimed to explore hub circadian rhythm-related genes (CRRGs) associated with sepsis-associated acute kidney injury (saAKI) using...