Journal Review in Surgical Education: Artificial Intelligence

Behind The Knife: The Surgery Podcast

With the increasing popularity of artificial intelligence, its uses are quickly becoming not only a part of everyday life, but also training in surgery. Those of us without much understanding of the technology might be intimidated by this nebulous topic, or worry that we won’t be able to comprehend the advancements to come to the field. Luckily, we’re joined by a leading expert in the use of AI in surgery, Dr. Dan Hashimoto. He breaks down some examples of how AI is being used in surgical education, the role surgeons should play in these advancements, and some tips for how we can critically appraise work in the field of AI if we don’t understand the technology ourselves. Join hosts Nicole Brooks, MD, Judith French, PhD and Jeremy Lipman, MD, MHPE for this exciting conversation.

Learning Objectives
1. Listeners will describe how AI is being applied to surgical education.
2. Listeners will identify the roles surgeons without training in AI can play in developing the use of AI in surgery.
3. Listeners will explain the regulatory and ethical considerations that must be addressed with the implementation of AI in surgical education.
4. Listeners will consider principles for critically evaluating research or technology in AI for application or use in their own educational or surgical practice.

References
Laplante S, Namazi B, Kiani P, Hashimoto DA, Alseidi A, Pasten M, Brunt LM, Gill S, Davis B, Bloom M, Pernar L, Okrainec A, Madani A. Validation of an artificial intelligence platform for the guidance of safe laparoscopic cholecystectomy. Surg Endosc. 2023 Mar;37(3):2260-2268. doi: 10.1007/s00464-022-09439-9. Epub 2022 Aug 2. PMID: 35918549.
https://pubmed.ncbi.nlm.nih.gov/35918549/

Hashimoto DA, Varas J, Schwartz TA. Practical Guide to Machine Learning and Artificial Intelligence in Surgical Education Research. JAMA Surg. 2024 Jan 3. doi: 10.1001/jamasurg.2023.6687. Epub ahead of print. PMID: 38170510.
https://pubmed.ncbi.nlm.nih.gov/38170510/

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