Urology

The nephrologist in the present and near future: between algorithms and autonomy.

This perspective examines how artificial intelligence (AI) may reshape nephrology over the next two decades while keeping the nephrologist's role central. Prediction models for acute kidney injury and chronic kidney disease progression, and multimodal tools such as KidneyIntelX, will deliver continuous, patient-level risk estimates from electronic health records, biomarkers, imaging, and wearable ...

Beyond Critical View of Safety: New Predictors of Objective Assessment of Critical View of Safety in Laparoscopic cholecystectomy-a Prospective Cohort Study.

BackgroundLaparoscopic cholecystectomy (LC) has revolutionised gallstone management. However, the incidence of bile duct injury (BDI) remains unchanged. Achieving the critical view of safety (CVS) is the standard endpoint of LC dissection to prevent BDI. This study aimed to identify preoperative, intraoperative, and novel predictors of CVS quality using intraoperative doublet photography.MethodsTh...

Artificial intelligence, surgical vision, and digital navigation in robotic urology: a bibliometric and knowledge-mapping analysis.

Digital technologies are increasingly used to extend the anatomical, functional, and procedural information available in robot-assisted urology, but t...

Perspective: The Future of Peritoneal Dialysis in the Era of Telemedicine and Artificial Intelligence.

Peritoneal dialysis (PD) represents one of the major modalities for home-based renal replacement therapy, offering autonomy and flexibility to patient...

Utility of ECG-Vision for Surveillance of Left Ventricular Dysfunction in Patients With Hypertrophic Cardiomyopathy Initiated on Mavacamten.

BACKGROUND: Frequent transthoracic echocardiograms (TTEs) are required to monitor for left ventricular systolic dysfunction (LVSD) in patients with ob...

Heterogeneous Treatment Effects of Renal Replacement Therapy in Critically Ill Patients: A Multicenter Observational Study Using a Japanese ICU Registry.

OBJECTIVE: Randomized trials evaluating the timing of renal replacement therapy (RRT) have informed current practice toward more conservative initiati...

Sex-specific associations of the bilirubin-to-albumin ratio with lung cancer risk: evidence from Cox regression and causal survival forest analysis.

BACKGROUND: The bilirubin-to-albumin (BA) ratio may reflect the balance between circulating bilirubin and albumin-related binding capacity, but its as...

Multimodal artificial intelligence for prostate cancer imaging: workflow-relevant fusion of mpMRI, PSMA PET, ultrasound, and clinical data for diagnosis, local staging, and treatment personalization.

BACKGROUND: Prostate cancer imaging is inherently multimodal, yet many AI tools remain single-modality and therefore misaligned with real-world abdomi...

Building a Natural Language Processing Augmented Information Support System to Enhance Supportive Care for Patients With Prostate Cancer and Families: User-Centered, Iterative Approach.

BACKGROUND: Patients with prostate cancer and their families face significant challenges during transitions from diagnosis to treatment and posttreatm...

Development and validation of a computational histology artificial intelligence-powered prognostic biomarker in muscle-invasive bladder cancer.

BACKGROUND: Patients with muscle-invasive bladder cancer (MIBC) have heterogeneous outcomes following transurethral resection of bladder tumor (TURBT)...

Construction and validation of a liquid neural network-based prediction model and bedside tool for spontaneous passage of common bile duct stones.

BACKGROUND: To construct and externally validate a liquid neural network (LNN)-based risk prediction model for spontaneous passage of common bile duct...

Autonomous AI in prostate cancer: the road ahead towards clinical implementation.

Artificial Intelligence (AI) for detecting clinically significant prostate cancer (csPCa) on MRI has achieved diagnostic performance comparable to tha...

Prediction models for adverse events from prostate cancer curative radiotherapy: a systematic review of methodological quality.

BACKGROUND: Predicting risks of urinary, bowel, sexual, and other adverse effects following prostate cancer curative radiotherapy (PCa-RT) is essentia...

An Organ-Guided Lightweight Multi-frame Integration Network for Real-Time Abdominal Lesion Detection in Ultrasound Video Streams.

OBJECTIVE: Abdominal ultrasound is widely used for the routine screening of hepatobiliary and renal diseases because it is safe, inexpensive and broad...

Machine learning-assisted prediction of 5-year mortality in chronic kidney disease: the KoreaN cohort study for Outcome in patients With Chronic Kidney Disease (KNOW-CKD).

BACKGROUND: Mortality prediction models for patients with non-dialysis chronic kidney disease (CKD) remain limited despite their clinical importance. ...

Interfractional Monitoring of Spacer Hydrogel Morphology in Patients With Prostate Cancer Receiving SBRT Treatment.

PURPOSE: The purpose of this study is to explore whether spacer hydrogel morphology changes during the course of stereotactic body radiation therapy (...

Risk analysis and warning model of post-noncardiac surgery acute kidney injury: A retrospective observational study.

Postoperative acute kidney injury (PO-AKI) following noncardiac surgery remains a major clinical challenge, for which effective early warning models a...

Accurate and noninvasive prostate cancer detection using plasma-derived extracellular vesicle RNA.

Prostate cancer (PCa) is the most commonly diagnosed noncutaneous malignancy in men and a leading cause of cancer-related death worldwide. Its clinica...

Urinary volatilomics using liquid-liquid extraction and gas chromatography-mass spectrometry (GC-MS) combined with machine learning algorithms as a tool for diagnosis and surveillance of urothelial bladder cancer.

BACKGROUND: Bladder cancer is the 11th most common cancer in the United Kingdom, with approximately 10,500 new cases annually. Diagnosis and surveilla...

Quality assessment of artificial intelligence responses in erectile dysfunction: a comparative study based on EAU recommendations.

Artificial intelligence (AI)-based language models are increasingly explored as tools for interpreting and applying clinical guideline recommendations...