Urology

Identification of acute kidney injury after non-cardiac surgery by machine learning leveraging a large electronic health record database.

Post-operative acute kidney injury (PO-AKI) is a frequent complication after non-cardiac surgery, substantially increasing patients' mortality and morbidity rates. Early identification of patients at high risk of PO-AKI could facilitate improved patient care. We investigated a large, single-center database of 13,890 patients undergoing non-cardiac surgery, of whom 1,718 (12.37%) developed PO-AKI. ...

Artificial intelligence in robotic urologic surgery: a scoping review.

BACKGROUND AND AIM: Artificial intelligence (AI) is increasingly being integrated into robotic urologic surgery. However, existing literature remains fragmented across different technological domains. This scoping review aimed to systematically map and synthesize current evidence on AI applications within robotic urologic surgery, identifying principal domains, clinical relevance, and existing lim...

Percutaneous thermal ablation for renal cell carcinoma: a comprehensive review of current evidence and future directions.

Thermal ablation (TA), including microwave ablation, radiofrequency ablation, and cryoablation, is increasingly used as a surgical alternative for T1a...

Prognostication in End-Stage Kidney Disease: Tools, Evidence, and Clinical Applications.

Prognostication in end-stage kidney disease is fundamental to person-centered care and shared decision-making. This review summarizes the current evid...

Nephrology 2050: an evidence-informed roadmap from precision prevention to kidney regeneration.

BACKGROUND: Chronic kidney disease (CKD) is projected to become one of the leading causes of premature mortality worldwide by 2050. Simultaneously, ad...

Prediction of pediatric lower urinary tract dysfunction using uroflowmetry data and machine learning with explainable AI techniques.

PURPOSE: To develop and evaluate a machine learning-based approach for the interpretation of uroflowmetry in pediatric lower urinary tract dysfunction...

ChatGPT-4o as a decision-support tool in a urological tumour board: a prospective evaluation.

PURPOSE: To evaluate ChatGPT-4o in a real-world urological multidisciplinary tumour board (MTB), with concordance for the final clinical recommendatio...

Interpretable Machine Learning for 30-Day Mortality in PIVSR: A Cohort Study.

OBJECTIVE: Post-infarction ventricular septal rupture (PIVSR) is a fatal mechanical complication of acute myocardial infarction. We aimed to develop a...

Unifying Phylogenetic Traversal and Deep Learning to Guide Tree Exploration.

Deep learning offers hope for more efficient phylogenetic inference methods. However, it has yet to have the transformative effect on phylogenetics th...

[Characteristics of urinary organic acid metabolic profile and screening of key metabolic markers in patients with urolithiasis].

OBJECTIVE: To systematically compare the differences in urinary organic acid metabolic profiles between patients with urinary calculi and non-calculi ...

Large language models and prostate MRI reporting: a stringent testbed for safe deployment under evolving AI, health-data, and cybersecurity regulation.

Prostate magnetic resonance imaging (MRI) reporting is a high-impact communication task because small differences in lesion laterality, sector localiz...

Comment on 'Artificial intelligence in the radiologic diagnosis of major urological cancers: a meta-analysis'.

A comprehensive framework for multi-class prostate cancer classification using biparametric MRI: a multi-center retrospective study.

OBJECTIVES: Accurate pre-biopsy or preoperative diagnosis and risk stratification of prostate cancer remain challenging. This study aimed to develop a...

Artificial intelligence for predicting BCG response in non-muscle-invasive bladder cancer: a systematic review.

OBJECTIVES: To systematically identify, appraise and synthesise artificial intelligence (AI) and machine-learning (ML) models that predict treatment r...

Diagnostic Model Development for IC/BPS and Its Subtypes Using Clinical Indicators, Urinary Biomarkers, and Single-Cell Transcriptomic Analysis.

Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic, heterogeneous, and often debilitating condition. This condition is often misdiagnos...

Deep learning-based automated identification of papillary bladder cancer from endoscopic still images using SE-ResNeXt-50.

Bladder cancer remains a major global health challenge, necessitating rigorous endoscopic surveillance and the precise identification of neoplastic le...

The role of magnetic resonance imaging in the active surveillance of prostate cancer: state of the art.

POURPOSE: To provide an update on the role of multiparametric magnetic resonance imaging (mpMRI) in active surveillance (AS) of prostate cancer, with ...

Impact of oncological biomarkers and clinical factors on survival outcomes in renal cell carcinoma with spinal metastasis: a retrospective analysis.

OBJECTIVE: Renal cell carcinoma (RCC) is a common malignancy that metastasizes to the spine, leading to complex treatment challenges and reduced survi...

Characterization of prostate MRI focal lesions by combining human reading, artificial intelligence and prostate-specific antigen density: A multi-reader study.

PURPOSE: The purpose of this study was to compare, across readers with varying experience, the characterisation of prostate MRI lesions as grade group...

Bibliometrics and visualization analysis: Big data research on diabetic kidney disease from 2000 to 2025.

BACKGROUND: As the prevalence of diabetes rises, diabetic kidney disease (DKD) has become a leading cause of end-stage renal disease. Big data analysi...