Artificial intelligence in surgery
Chris Varghesea, Ewen Munro Harrisonb, Greg O’Gradya c, Eric J. Topold e✉
- aDepartment of Surgery, University of Auckland, Auckland, New Zealand
- bCentre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK
- cAuckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- dScripps Research Translational Institute, La Jolla, CA, USA. etopol@scripps.edu
- eScripps Research Translational Institute, La Jolla, CA, USA
- ✉Corresponding author
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Abstract
Artificial intelligence (AI) is rapidly emerging in healthcare, yet applications in surgery remain relatively nascent. Here we review the integration of AI in the field of surgery, centering our discussion on multifaceted improvements in surgical care in the preoperative, intraoperative and postoperative space. The emergence of foundation model architectures, wearable technologies and improving surgical data infrastructures is enabling rapid advances in AI interventions and utility. We discuss how maturing AI methods hold the potential to improve patient outcomes, facilitate surgical education and optimize surgical care. We review the current applications of deep learning approaches and outline a vision for future advances through multimodal foundation models.
TL;DRThe state of the art of artificial intelligence in the preoperative, intraoperative and postoperative settings, where it has enormous potential to improve patient outcomes, surgical education and system efficiencies is outlined. (Semantic Scholar)