Urology

Deep learning-based quantitative assessment of renal chronicity indices in lupus nephritis.

Renal chronicity indices (CI) have been identified as strong predictors of long-term outcomes in lupus nephritis (LN) patients. However, assessment by pathologists is hindered by challenges such as substantial time requirements, high interobserver variation, and susceptibility to fatigue. This study aims to develop an effective deep learning (DL) pipeline that automates the assessment of CI and pr...

Determining the Survival Impact and Cost-Effectiveness of Multi-Gene Panel Sequencing in Metastatic Colorectal Cancer With Super Learning Approaches.

OBJECTIVE: To determine the effectiveness and cost-effectiveness of multi-gene panel sequencing compared to single-gene KRAS testing for metastatic colorectal cancer (mCRC). STUDY SETTING AND DESIGN: British Columbia, Canada (BC) is a provincial single-payer public healthcare system, and it was the first province to publicly reimburse multi-gene sequencing for mCRC. Panels expand treatment de-esca...

Predicting and Optimizing Synergistic Drug Combinations for Breast Cancer Treatment Using Machine Learning.

OBJECTIVES: The study aims to identify highly synergistic drug combinations for breast cancer treatment using machine learning models. The primary obj...

Portrayal of Cancer Patients in the Era of AI: A Content Analysis of Images Produced by Generative AI Tools.

This study sought to characterize images of cancer patients generated by Artificial Intelligence (AI) text-to-image tools, and assess whether images d...

Repeatability and Reproducibility of Artificial Imaging-based Digital Pathology for the Evaluation of Liver Fibrosis.

BACKGROUND & AIMS: Fibrosis stage is a key determinant of outcomes in metabolic dysfunction-associated steatohepatitis (MASH). Assessment of fibrosis ...

Machine learning-based MRI imaging for prostate cancer diagnosis: systematic review and meta-analysis.

OBJECTIVE: This study aims to evaluate the diagnostic value of machine learning-based MRI imaging in differentiating benign and malignant prostate can...

Tissue perfusion pressure: A novel hemodynamic measure to assess risk of acute kidney injury after cardiac surgery.

BACKGROUND: Optimal hemodynamic targets for preventing acute kidney injury (AKI) have remained elusive. We hypothesized that lower tissue perfusion pr...

Impact of three-dimensional prostate models during robot-assisted radical prostatectomy on surgical margins and functional outcomes.

BACKGROUND: Robot-assisted radical prostatectomy (RARP) is the standard surgical procedure for the treatment of prostate cancer. RARP requires a trade...

Machine learning-based prediction of stone-free rate after retrograde intrarenal surgery for lower pole renal stones.

BACKGROUND: Lower pole renal stones (LPS) present unique challenges for retrograde intrarenal surgery (RIRS) due to unfavorable anatomical features, o...

AI-driven robotic surgery in oncology: advancing precision, personalization, and patient outcomes.

Artificial intelligence (AI) integrated with robotic systems is transforming oncologic surgery by significantly improving precision, safety, and perso...

Identification and validation of epithelial‑mesenchymal transition‑related genes for diabetic nephropathy by WGCNA and machine learning.

Diabetic nephropathy (DN) is the main cause of end‑stage renal disease, with epithelial‑mesenchymal transition (EMT) serving a key role in its initiat...

Current state of AI for shockwave lithotripsy: a systematic review from YAU and EAU endourology.

PURPOSE: To consolidate the current evidence of artificial intelligence (AI) for management of nephrolithiasis using extracorporeal shock-wave lithotr...

Current Applications and Limitations of Augmented Reality in Urological Surgery: A Practical Primer and 'State of the Field'.

PURPOSE OF REVIEW: To provide a primer for how augmented reality (AR)-guided surgical technology works at a fundamental level and discuss recent advan...

Picoeukaryote-based biohybrid microrobots for active delivery in the kidney.

Confined spaces in the human body pose substantial challenges for biomedical procedures. Navigating these ultrasmall environments is essential for pre...

Modelling key ecological factors influencing the distribution and content of silymarin antioxidant in Silybum marianum L.

The increasing demand for natural medicine has increased the significance of Silybum marianum as a valuable medicinal plant. It is used to restore liv...

Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.

OBJECTIVE: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, with chronic inflammation driving its progression. This study a...

Deep learning to assess erythritol in zebrafish development, circadian rhythm, and cardiovascular disease risk.

Erythritol is one of the most widely used artificial sweeteners, yet the potential risks remain a subject of debate. In this experiment, the concentra...

AI based natural inhibitor targeting RPS20 for colorectal cancer treatment using integrated computational approaches.

The increasing global incidence of cancer emphasizes the vital role of machine learning algorithms and artificial intelligence (AI) in identifying nov...

Automatic recognition of surgical phase of robot-assisted radical prostatectomy based on artificial intelligence deep-learning model and its application in surgical skill evaluation: a joint study of 18 medical education centers.

BACKGROUND: Surgical proficiency influences surgical quality and patient outcomes in robot-assisted radical prostatectomy (RARP). Manual video evaluat...

High-throughput LDI MS technology decodes the distinct metabolic landscape of prostate cancer in a large-scale cohort.

BACKGROUND: Prostate cancer (PCa) remains a leading global malignancy, yet current diagnostic reliance on prostate-specific antigen (PSA) testing is l...