OBJECTIVE: With the increased adoption of robotic pancreaticoduodenectomy, the effects of unplanned conversions to an 'open' operation are ill-defined. This study aims to describe the impact of unplanned conversions of robotic pancreaticoduodenectomy...
BACKGROUND: In the era of minimally invasive surgery, it is clear that a robust simulation model is required for the training of surgeons in advanced abdominal wall reconstruction. The purpose of this experimentation was to evaluate whether a porcine...
BACKGROUND: In laparoscopic right hemicolectomy (RHC) for right-sided colon cancer, accurate recognition of the vascular anatomy is required for appropriate lymph node harvesting and safe operative procedures. We aimed to develop a deep learning mode...
BACKGROUND: Video-based review is paramount for operative performance assessment but can be laborious when performed manually. Hierarchical Task Analysis (HTA) is a well-known method that divides any procedure into phases, steps, and tasks. HTA requi...
BACKGROUND: Using a validated, objective, and standardised assessment tool to assess progression and competency is essential for basic robotic surgical training programmes. Objective clinical human reliability analysis (OCHRA) is an error-based asses...
BACKGROUND: The surgical resection of rectal carcinoma is associated with a high risk of permanent stoma rate. Primary anastomosis rate is suggested to be higher in robot-assisted and transanal total mesorectal excision, but permanent stoma rate is u...
BACKGROUND: We compared surgeons' workload, physical discomfort, and neuromusculoskeletal disorders (NMSDs) across four surgical modalities: endoscopic, laparoscopic, open, and robot-assisted (da Vinci Surgical Systems).
BACKGROUND: Currently, only a limited number of remote assistance modalities are utilized in the basic phase of robotic surgery training to facilitate the rapid acquisition of robotic surgery skills by surgeons. This study aimed to investigate the be...
BACKGROUND: With Surgomics, we aim for personalized prediction of the patient's surgical outcome using machine-learning (ML) on multimodal intraoperative data to extract surgomic features as surgical process characteristics. As high-quality annotatio...
BACKGROUND: The increased digitization in robotic surgical procedures today enables surgeons to quantify their movements through data captured directly from the robotic system. These calculations, called objective performance indicators (OPIs), offer...