Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks

Jin, Amy; Yeung, Serena; Jopling, Jeffrey; Krause, Jonathan; Azagury, Dan E.; Milstein, Arnold; Li, Feifei

doi:10.48550/arxiv.1802.08774

Cited by 2 publications

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Use of artificial intelligence in total mesorectal excision in rectal cancer surgery: State of the art and perspectives

Mosca,

Fuschillo,

Sciaudone

et al. 2023

Artif Intell Gastroenterol

View full text Add to dashboard Cite

BACKGROUND Colorectal cancer is a major public health problem, with 1.9 million new cases and 953000 deaths worldwide in 2020. Total mesorectal excision (TME) is the standard of care for the treatment of rectal cancer and is crucial to prevent local recurrence, but it is a technically challenging surgery. The use of artificial intelligence (AI) could help improve the performance and safety of TME surgery. AIM To review the literature on the use of AI and machine learning in rectal surgery and potential future developments. METHODS Online scientific databases were searched for articles on the use of AI in rectal cancer surgery between 2020 and 2023. RESULTS The literature search yielded 876 results, and only 13 studies were selected for review. The use of AI in rectal cancer surgery and specifically in TME is a rapidly evolving field. There are a number of different AI algorithms that have been developed for use in TME, including algorithms for instrument detection, anatomical structure identification, and image-guided navigation systems. CONCLUSION AI has the potential to revolutionize TME surgery by providing real-time surgical guidance, preventing complications, and improving training. However, further research is needed to fully understand the benefits and risks of AI in TME surgery.

show abstract