PURPOSE: This multi-institutional study aimed to assess the outcomes of laparoscopic ureterocalicostomy (LUC) and robot-assisted laparoscopic ureterocalicostomy (RALUC) and compare them with laparoscopic pyeloplasty (LP) and robot-assisted laparoscop...
PURPOSE: We investigated the feasibility of measuring the hydronephrosis area to renal parenchyma (HARP) ratio from ultrasound images using a deep-learning network.
INTRODUCTION: With the advent of robot-assisted laparoscopic ureteral reimplantation (RALUR) for primary vesicoureteral reflux (VUR), understanding and minimizing its complications continues to be critical. Incidence of de novo hydronephrosis after R...
INTRODUCTION: The aim of the study was to elucidate the predictive and prognostic value of serum gamma-glutamyltransferase (GGT) in patients with invasive bladder cancer (BC).
The Urologic clinics of North America
Oct 23, 2021
The growth and adoption of artificial intelligence has led to impressive results in urology. As artificial intelligence grows more ubiquitous, it is important to establish artificial intelligence literacy in the workforce. To this end, we present a n...
PURPOSE: Hydronephrosis is the dilation of the pelvicalyceal system due to the urine flow obstruction in one or both kidneys. Conventionally, renal pelvis anterior-posterior diameter (APD) was used for quantifying hydronephrosis in medical images (e....
OBJECTIVE: To reliably and quickly diagnose children with posterior urethral valves (PUV), we developed a multi-instance deep learning method to automate image analysis.
BACKGROUND: Significant amounts of health data are stored as free-text within clinical reports, letters, discharge summaries and notes. Busy clinicians have limited time to read such large amounts of free-text and are at risk of information overload ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.