Latest Advancement in Medical Surgery using Artificial Intelligence

TLDR

This work has shown that the integration of multiple computer vision models, such as Dinov2 and the latest YOLOv9, with balanced classes, holds the potential to address existing challenges in the accuracy and real-time identification of instruments and organs.

摘要

Recent advancements in artificial intelligence (AI) have significantly enhanced the use of computer vision, machine learning, natural language processing, augmented reality, and deep learning in surgical video analysis. Laparoscopic procedures generate vast amounts of video data, presenting opportunities for AI to support real-time decision-making and improve surgeon training. AI-based computer vision techniques can extract valuable insights from these videos, facilitating precise intraoperative decisions and enhancing educational systems. Key applications of AI in surgery include robotic surgery, image- guided interventions, and instrument tracking. Emerging fields like automatic surgical action prediction and tool identification are gaining prominence, aiming to refine real-time support systems. The integration of multiple computer vision models, such as Dinov2 and the latest YOLOv9, with balanced classes, holds the potential to address existing challenges in the accuracy and real-time identification of instruments and organs. Future research should focus on further developing these AI applications and utilizing them for more effective surgical training and skill evaluation.