Urology

Prognostic value of estimated pulse wave velocity for all-cause and cardiovascular mortality in individuals with cardiovascular-kidney-metabolic (CKM) syndrome: analyses of NHANES 2007-2018.

BACKGROUND: The impact of estimated pulse wave velocity (ePWV) on the prognosis of cardiovascular-kidney-metabolic (CKM) syndrome has not been explored. This study investigated the association between ePWV and mortality and its predictive performance in individuals with CKM syndrome. METHODS: This population-based prospective study of 9,416 American participants used ordinal logistic regression to...

Phenotyping Preeclampsia Using Unsupervised Machine Learning: A Prospective Cohort Study.

OBJECTIVE: To explore clinically meaningful phenotypes of preeclampsia using unsupervised machine learning. DESIGN: Prospective cohort study. SETTING: BCNatal, a tertiary maternal-foetal medicine centre (Barcelona, Spain). POPULATION: A total of 482 pregnant women diagnosed with preeclampsia between August 2013 and April 2024. METHODS: Maternal demographic, clinical, ultrasound and laboratory data...

Performance and Utility of the Sybil Deep Learning Model for Lung Cancer Risk Prediction in Asian High- and Low-Risk Populations.

BACKGROUND: Sybil is a deep learning model designed to predict future lung cancer risk based on a single low-dose chest CT (LDCT) scan, facilitating a...

Artificial intelligence in small tissue biopsies: diagnostic applications, histochemical integration, and methodological challenges in surgical pathology.

Small tissue biopsies, including renal core biopsies, bone marrow trephines, gastrointestinal endoscopic samples, prostate needle cores, liver biopsie...

A Bioinspired Three-Dimensional High-Curvature Nano-Interface Integrated Microfluidic Chip for Small Extracellular Vesicles Enrichment and Machine Learning-Assisted Prostate Cancer Precision Diagnosis.

The efficient and unbiased isolation of small extracellular vesicles (sEVs) from complex biological fluids remains a major obstacle for clinical diagn...

From Flow to Feature Using a Proof-of-Concept Spectral-Driven Machine Learning Approach Using Smart Urinary and Drainage Catheter Systems: Algorithm Development and Validation.

BACKGROUND: Current urinary and drainage catheter systems collect fluids for visual inspection or manual sampling, offering limited diagnostic value w...

Generative AI-Assisted Microlearning for Erectile Dysfunction Myth Reduction: Single-Center Pre-Post Quasi-Experimental Study.

BACKGROUND: Erectile dysfunction (ED) is strongly influenced by persistent misconceptions that delay help-seeking and limit engagement with effective ...

A probabilistic framework for risk-bounded patient-specific quality assurance in volumetric modulated arc therapy based on measured and calculated gamma pass rates.

This study introduces a probabilistic framework for patient-specific quality assurance (PSQA) in volumetric modulated arc therapy (VMAT), using gamma ...

Randomized trial of electronic health record implemented AI risk prediction in kidney transplant care.

Artificial intelligence (AI)-based risk prediction is increasingly implemented in clinical care, but randomized evidence on communication and shared d...

Predicting anemia treatment outcomes in maintenance hemodialysis patients using multiple machine learning models.

BACKGROUND: Based on machine learning prediction models, we explored the anemia treatment attainment of patients on maintenance hemodialysis (MHD) and...

[Artificial intelligence as decision support tool in urological oncology: current evidence and challenges].

BACKGROUND: The rising incidence of cancer, increasing life expectancy and complex personalized treatment concepts pose considerable challenges for th...

Dual-conditioned diffusion model with anatomical guidance for geometric distortion correction in prostate MRI.

OBJECTIVE: Geometric distortion from susceptibility artifacts in diffusion-weighted imaging (DWI) degrades anatomical fidelity and complicates clinica...

Two decades of robotic pediatric urology: a single-surgeon evolution from adoption to excellence.

The establishment of a Center of Excellence in robotic pediatric urology is a deliberate, phased evolution-from individual pioneering procedures to an...

Semen RNA-Based Biomarkers for Prostate Cancer Detection and Risk Stratification: A Prospective Multi-Center Validation Study.

OBJECTIVE: To assess the diagnostic performance of semen RNA-based biomarkers for detecting prostate cancer and differentiating cancer grade groups. M...

Deep learning-based intraluminal gas modeling for anatomically accurate synthetic CT in MRI-based radiation therapy.

Stochastic bowel and rectal gas complicates MRI/CT deformable image registration (DIR) for synthetic CT (sCT) generation, requiring manual corrections...

Performance of large language models (GPT-5.2, Gemini 3 Pro, Claude Sonnet 4.6 and Grok 4.1) on the Fellowship of The Royal College of Surgeons Urology Part A examination.

OBJECTIVES: To assess and compare the performance of four contemporary frontier large language models (LLMs)-GPT-5.2 (OpenAI), Gemini 3 Pro (Google De...

The impact of tissue detection on diagnostic artificial intelligence algorithms in prostate digital pathology.

Tissue detection is a crucial first step in most digital pathology applications. By applying image segmentation algorithms, all tissue is delineated a...

Bladder cancer segmentation using u-net-based deep-learning.

We are developing a decision support system for treatment response assessment of bladder cancer by analyzing patients' CT urography (CTU) examinations...

Deep-learning time-series anomaly detection of acute kidney injury from creatinine-eGFR trajectories in the ICU.

Acute kidney injury (AKI) is common in the intensive care unit (ICU), and fixed creatinine thresholds may miss clinically relevant dynamics. We tested...

Machine learning model predicts acute kidney injury in pediatric patients after cardiac surgery: a systematic review and meta-analysis.

BACKGROUND: Acute kidney injury (AKI) is a common complication following pediatric cardiac surgery, frequently leading to poor outcomes and even death...