PURPOSE: Despite the high incidence of perioperative complications following cystectomy, there is a lack of evidence regarding patients' perceptions. Moreover, discrepancies between established complication grading systems and the patient's perspecti...
OBJECTIVE: To assess the role of neoadjuvant chemotherapy (NAC) before robot-assisted radical cystectomy (RARC) for patients with variant histology (VH) muscle-invasive bladder cancer (MIBC).
INTRODUCTION: This study was performed to evaluate the differences in the perioperative results, renal function, and incidence of hydronephrosis over time between the use of Bricker anastomosis and Wallace anastomosis for robot-assisted intracorporea...
BACKGROUND: Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated wit...
BACKGROUND: Prediction models based on machine learning (ML) methods are being increasingly developed and adopted in health care. However, these models may be prone to bias and considered unfair if they demonstrate variable performance in population ...
PURPOSE: We aimed to use a validated artificial intelligence (AI) algorithm to extract muscle and adipose areas from CT images before radical cystectomy (RCx) and then correlate these measures with 90-day post-RCx complications.
PURPOSE: There are few markers to identify those likely to recur or progress after treatment with intravesical bacillus Calmette-Guérin (BCG). We developed and validated artificial intelligence (AI)-based histologic assays that extract interpretable ...
BACKGROUND: Accurately assessing the prognosis of bladder cancer patients after radical cystectomy has important clinical and research implications. Current models, based on traditional statistical approaches and complex variables, have limited perfo...
Artificial intelligence (AI)-driven intraoperative navigation in urological surgery can enhance surgical precision through real-time structure identification and tracking. This study describes a novel AI solution that enables real-time fluorescence-l...