Urology

Applying machine learning to pharmacovigilance data: A proof-of-concept study.

AIM: Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance database (FNPV), this proof-of-concept study aimed to assess the feasibility of using a ML algorithm-eXtreme Gradient Boosting (XGBoost)-combined with SHapley Additive exPlanations (SHAP) analysis, to classify a well-defined drug-adverse reaction pair...

Predicting PPOI secondary to laparoscopic radical resection of rectal cancer combined with lobaplatin hyperthermic intraperitoneal chemotherapy: a multi-center study.

PURPOSE: PPOI is one of the common complications of intraperitoneal hyperthermic chemotherapy during laparoscopic radical resection of rectal cancer, which seriously affects the prognosis of patients. The purpose of this study is to establish a prediction system for PPOI secondary to laparoscopic radical resection of rectal cancer combined with intraperitoneal hyperthermic chemotherapy with lobapl...

Contrast injection protocols used in oncological CT and opportunities for practice optimisation.

INTRODUCTION: Contrast-enhanced CT is central to oncological imaging, yet no official guidelines exist for contrast injection protocols. As a result, ...

Uncertainty-aware 3D tumor segmentation with deep ensembles: an evaluation of temporal versus data diversity.

Artificial intelligence (AI) is transforming segmentation tasks in radiotherapy, but model reliability remains a critical concern, particularly for tu...

Single-cell transcriptomic analysis reveals the T lymphocyte microenvironment and identifies HOPX as a hub gene in membranous nephropathy.

BACKGROUND: Membranous nephropathy (MN) is an autoimmune disease characterized by immune complex deposition and progressive renal function impairment....

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) inter...

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 repe...

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...