PURPOSE: To assess the effectiveness of a deep learning model using contrastenhanced ultrasound (CEUS) images in distinguishing between low-grade (grade I and II) and high-grade (grade III and IV) clear cell renal cell carcinoma (ccRCC).
OBJECTIVE: To investigate the safety and feasibility of using a novel purpose-built single-port robotic system (the SHURUI Robotic Surgical System) with deformable surgical instruments to perform retroperitoneal single-port partial nephrectomy.
BACKGROUND: The rise of artificial intelligence (AI) in medicine has revealed the potential of ChatGPT as a pivotal tool in medical diagnosis and treatment. This study assesses the efficacy of ChatGPT versions 3.5 and 4.0 in addressing renal cell car...
The influence of chronic kidney disease stage on robot-assisted partial nephrectomy outcomes remains underexplored. This study aimed to assess the impact of chronic kidney disease stage on functional and surgical outcomes of robot-assisted partial ne...
Robot-assisted partial nephrectomy (RAPN) has rapidly evolved as the standard of care for appropriately selected renal tumours, offering key patient benefits over radical nephrectomy or open surgical approaches. Accordingly, RAPN is a key competency ...
Complete endophytic renal tumors (CERTs) are the most challenging for robot-assisted partial nephrectomy (RAPN). This study aimed to determine the impact of CERT on outcomes of RAPN. All RAPN cases for localized renal tumor undertaken at Yokohama C...
OBJECTIVE: This study analyzes the potential cost-effectiveness of integrating an artificial intelligence (AI)-assisted system into the differentiation of incidental renal lesions as benign or malignant on MR images during follow-up.
To evaluate the recurrence rate and risk factors of recurrence after robot-assisted laparoscopic partial nephrectomy for solitary renal cell carcinoma (RCC). A total of 1265 cases of initial solitary localized RCC were analyzed. The baseline characte...
INTRODUCTION: Accurate diagnosis and treatment of kidney tumors greatly benefit from automated solutions for detection and classification on MRI. In this study, we explore the application of a deep learning algorithm, YOLOv7, for detecting kidney tum...
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