Latest AI and machine learning research in urology for healthcare professionals.
Accurate segmentation of kidney in ultrasound images is a vital procedure in clinical diagnosis and ...
Urinary-based infections affect millions of people worldwide. Such bacterial infections are mainly c...
The high quality of MRI reporting of the prostate is the most critical component of the service prov...
PURPOSE: Robot-assisted partial nephrectomy (RAPN) for posterior renal tumors may be performed throu...
OBJECTIVES: Purely hilar lesions and those abutting the main renal artery or vein may be significant...
INTRODUCTION: Prophylactic urethrectomy is often performed simultaneously with radical cystectomy (R...
For large prostate volume, open simple prostatectomy (OSP) or holmium laser enucleation are the gold...
PURPOSE: Radical cystectomy (RC) with urinary diversion (UD) is still considered a complex surgery a...
Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diff...
PURPOSE: To present fully automated DL-based prostate cancer detection system for prostate MRI.
BACKGROUND: The evaluation of automatic segmentation algorithms is commonly performed using geometri...
This study was aimed at analyzing the diagnostic value of convolutional neural network models on acc...
We assessed whether the severity of anastomotic urinary leakage detected during routine cystourethro...
OBJECTIVES: Radical cystectomy (RC) represents the gold standard treatment for high-risk bladder can...
This study evaluates the difference of robot-assisted radical prostatectomy (RARP) costs in patients...
LITERATURE REVIEW: Cystoscopy is the gold standard for initial macroscopic assessments of the human ...
Optimal management of duplication anomalies may include an upper or lower tract surgical approach. I...
BACKGROUND: We investigated the effect of the extent of pelvic lymph node dissection (LND) on bioche...
OBJECTIVE: To distinguish benign from malignant cystic renal lesions (CRL) using a contrast-enhanced...
Weakly supervised learning has emerged as an appealing alternative to alleviate the need for large l...