Utilizing Artificial Intelligence for Workflow Assessment in Robotic Excision of Choledochal Cysts: A Preliminary Investigation

Category	Detail
Condition	Robotic Excision of Choledochal Cysts
Key Mechanisms	Artificial intelligence integrated with surgical data science for phase recognition and workflow assessment.
Target Population	Children and adults undergoing robotic surgery for choledochal cysts.
Care Setting	Robotic surgery in a clinical environment.

Robotic surgery enhances minimally invasive reconstruction with advanced visualization and instrumentation.
AI can automate recognition of surgical phases, improving assessment of operative performance.
The study developed a model to quantify workflow variations in robotic CC surgery.
Longer dissection phases may correlate with increased intraoperative burden.
The investigation aims to provide insights into workflow differences related to age and anatomy.

Pediatric and adult patients undergoing robotic excision of choledochal cysts.

AI-derived phase durations could yield clinically meaningful workflow information.

Utilize AI for automated phase recognition to enhance surgical workflow assessment.
Standardize operative workflows to facilitate consistent evaluation of robotic procedures.
Incorporate phase-based assessments to identify determinants of operative duration.

Clinical Scorecard: Utilizing Artificial Intelligence for Workflow Assessment in Robotic Excision of Choledochal Cysts: A Preliminary Investigation