Keywords
Deep learning;
Laparoscopic cholecystectomy.
Abstract
Introduction: Laparoscopic cholecystectomy (LC) was a major advance in the management of cholelithiasis and cholecystitis, and is now considered an introductory-level endoscopic surgery. Despite low complications, bile duct injury in LC is significant. Artificial intelligence (AI) is a technology based on the use of algorithms to simulate human cognitive functions. This study explored the application of this technology in laparoscopic cholecystectomies. Objective: To analyze the applications of artificial intelligence in laparoscopic cholecystectomies and its impact on procedural safety. Methodology: A systematic literature review was carried out following the PRISMA recommendations and PECO criteria using the PubMed academic database. Results: AI demonstrated accuracy in critical tasks during cholecystectomies, such as anatomical recognition and the identification of surgical stages, showing potential to enhance the safety of laparoscopic cholecystectomy and reduce the incidence of bile duct injuries during the procedure. Discussion: The findings indicate that AI is a viable tool to assist in surgical practice. Through real-time feedback, this technology contributes to the improvement of technical skills, the reduction of errors, and decision-making support, thereby promoting better surgical performance and greater operative safety. Conclusion: It is evident that the evolution of technology and medicine has enabled the association between AI and CL. This integration is capable of increasing performance and being used to support medical decisions, as well as reducing surgical risks.