BACKGROUND: Few data are available to assess the learning curve for robotic-assisted surgery for rectal cancer. The aim of the present study was to evaluate the learning curve for robotic-assisted surgery for rectal cancer by a surgeon at a single in...
BACKGROUND: Simple enucleation (SE) has proven to be oncologically safe. We describe the surgical steps and report the results of the Endoscopic Robotic-Assisted Simple Enucleation (ERASE) technique.
INTRODUCTION: Intrarenal tumors pose a unique challenge to surgeons due to the lack of visual cues on the kidney surface. Intraoperative ultrasonography has facilitated the management of these tumors during minimally invasive partial nephrectomy. We ...
BACKGROUND: We have previously reported that laparoscopic approach improved short-term postoperative courses even for advanced gastric adenocarcinoma, but not morbidity, in comparison with open approach. The objective of this study was to determine t...
BACKGROUND: Laparoscopy offers some evidence of benefit compared to open rectal surgery. Robotic rectal surgery is evolving into an accepted approach. The objective was to analyze and compare laparoscopic and robotic rectal surgery learning curves wi...
OBJECTIVES/HYPOTHESIS: New approaches for robotic-assisted thyroidectomy, including the retroauricular approach, were recently described. We have modified the established surgical approach for retroauricular robotic thyroidectomy. Herein, we report o...
BACKGROUND: We report the operative details and short term oncologic and functional outcome of the first 334 Robotic-assisted radical prostatectomy experiences for organ confined prostate cancer
BACKGROUND: Accurate prediction of surgical duration is critical to optimizing use of operating room resources. Currently, cases are scheduled using subjective estimates of length by surgeons, relying heavily on prior experience. This study aims to d...
PURPOSE: To investigate the factors influencing the length of percutaneous nephrolithotomy (PCNL) procedures and identify predictive variables for operation time using machine learning models.
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