Generative artificial intelligence in surgery

Severin Rodler; Conner Ganjavi; Pieter De Backer; Vasileios Magoulianitis; Lorenzo Storino Ramacciotti; Andre Luis De Castro Abreu; Inderbir S Gill; Giovanni E Cacciamani

doi:10.1016/j.surg.2024.02.019

Generative artificial intelligence in surgery

Surgery. 2024 Apr 5:S0039-6060(24)00119-3. doi: 10.1016/j.surg.2024.02.019. Online ahead of print.

Authors

Severin Rodler¹, Conner Ganjavi², Pieter De Backer³, Vasileios Magoulianitis⁴, Lorenzo Storino Ramacciotti², Andre Luis De Castro Abreu², Inderbir S Gill², Giovanni E Cacciamani⁵

Affiliations

¹ USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA; Artificial Intelligence Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA; Department of Urology, University Hospital of LMU Munich, Germany; Young Academic Working Group in Urologic Technology of the European Association of Urology, Arnhem, The Netherlands.
² USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA; Artificial Intelligence Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA.
³ Young Academic Working Group in Urologic Technology of the European Association of Urology, Arnhem, The Netherlands; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium; ORSI Academy, Ghent, Belgium.
⁴ Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA.
⁵ USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA; Artificial Intelligence Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA; Young Academic Working Group in Urologic Technology of the European Association of Urology, Arnhem, The Netherlands. Electronic address: giovanni.cacciamani@med.usc.edu.

PMID: 38582732
DOI: 10.1016/j.surg.2024.02.019

Abstract

Generative artificial intelligence is able to collect, extract, digest, and generate information in an understandable way for humans. As the first surgical applications of generative artificial intelligence are applied, this perspective paper aims to provide a comprehensive overview of current applications and future perspectives for the application of generative artificial intelligence in surgery, from preoperative planning to training. Generative artificial intelligence can be used before surgery for planning and decision support by extracting patient information and providing patients with information and simulation regarding the procedure. Intraoperatively, generative artificial intelligence can document data that is normally not captured as intraoperative adverse events or provide information to help decision-making. Postoperatively, GAIs can help with patient discharge and follow-up. The ability to provide real-time feedback and store it for later review is an important capability of GAIs. GAI applications are emerging as highly specialized, task-specific tools for tasks such as data extraction, synthesis, presentation, and communication within the realm of surgery. GAIs have the potential to play a pivotal role in facilitating interaction between surgeons and artificial intelligence.

Publication types

Review