Andrew A. Gumbs
Artificial intelligence surgery: how do we get to autonomous actions in surgery?
Gumbs, Andrew A.; Frigerio, Isabella; Spolverato, Gaya; Croner, Roland; Illanes, Alfredo; Chouillard, Elie; Elyan, Eyad
Professor Eyad Elyan firstname.lastname@example.org
Most surgeons are skeptical as to the feasibility of autonomous actions in surgery. Interestingly, many examples of autonomous actions already exist and have been around for years. Since the beginning of this millennium, the field of artificial intelligence (AI) has grown exponentially with the development of machine learning (ML), deep learning (DL), computer vision (CV) and natural language processing (NLP). All of these facets of AI will be fundamental to the development of more autonomous actions in surgery, unfortunately, only a limited number of surgeons have or seek expertise in this rapidly evolving field. As opposed to AI in medicine, AI surgery (AIS) involves autonomous movements. Fortuitously, as the field of robotics in surgery has improved, more surgeons are becoming interested in technology and the potential of autonomous actions in procedures such as interventional radiology, endoscopy and surgery. The lack of haptics, or the sensation of touch, has hindered the wider adoption of robotics by many surgeons; however, now that the true potential of robotics can be comprehended, the embracing of AI by the surgical community is more important than ever before. Although current complete surgical systems are mainly only examples of tele-manipulation, for surgeons to get to more autonomously functioning robots, haptics is perhaps not the most important aspect. If the goal is for robots to ultimately become more and more independent, perhaps research should not focus on the concept of haptics as it is perceived by humans, and the focus should be on haptics as it is perceived by robots/computers. This article will discuss aspects of ML, DL, CV and NLP as they pertain to the modern practice of surgery, with a focus on current AI issues and advances that will enable us to get to more autonomous actions in surgery. Ultimately, there may be a paradigm shift that needs to occur in the surgical community as more surgeons with expertise in AI may be needed to fully unlock the potential of AIS in a safe, efficacious and timely manner.
GUMBS, A.A., FRIGERIO, I., SPOLVERATO, G., CRONER, R., ILLANES, A., CHOUILLARD, E. and ELYAN, E. 2021. Artificial intelligence surgery: how do we get to autonomous actions in surgery? Sensors [online], 21(16), article 5526. Available from: https://doi.org/10.3390/s21165526
|Journal Article Type||Article|
|Acceptance Date||Aug 11, 2021|
|Online Publication Date||Aug 17, 2021|
|Publication Date||Aug 31, 2021|
|Deposit Date||Aug 30, 2021|
|Publicly Available Date||Aug 30, 2021|
|Peer Reviewed||Peer Reviewed|
|Keywords||Artificial intelligence surgery; Autonomous robotics; Machine learning; Deep learning; Computer vision; Natural language processing|
GUMBS 2021 Artificial intelligence
Publisher Licence URL
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
You might also like
A data-driven decision support tool for offshore oil and gas decommissioning.
A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams.
Class-decomposition and augmentation for imbalanced data sentiment analysis.
Face detection with YOLO on edge.