Journal Review in Surgical Education: Artificial Intelligence
Mar 18, 2024
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Expert Dr. Dan Hashimoto discusses the role of AI in surgical education. Topics include deep learning, collaboration between surgeons and engineers, ethical considerations, research methodology in AI, and the importance of AI education in medical training.
AI in surgery enhances education by analyzing trainees' performance through video and text entries.
Surgeons must collaborate with AI experts to ensure safe and meaningful utilization of AI tools in surgery.
Deep dives
Applications of AI in Surgical Education
The podcast explores the advancements of artificial intelligence (AI) in surgery and surgical education. Dr. Dan Hashimoto discusses the use of AI to enhance surgical educational methods by analyzing video and text entries. The discussion highlights the potential of AI to provide quantitative analysis of trainees' performance using various data sources, such as video recordings and EMR notes. The application of AI in surgery aims to improve decision-making processes and offer personalized feedback to trainees.
Surgeons' Role in AI Integration
Dr. Hashimoto emphasizes the importance of surgeons leveraging their expertise in clinical care when incorporating AI technology. Surgeons are encouraged to focus on patient care impact, trainee development, and workflow integration while collaborating with AI experts. The discussion underscores the need for surgeons to actively engage in dialogue with technology developers to ensure safe and meaningful utilization of AI tools in surgery.
Interoperative AI Projects and Decision Support
The podcast highlights projects like the GoNoGoNet utilizing AI for intraoperative decision-making support during surgical procedures. The conversation delves into how AI algorithms can assist surgeons in identifying safe and unsafe dissection zones. The discussion underscores the collaborative nature of AI integration in real-time operative settings for augmenting decision-making rather than replacing surgical skills.
Ethical and Legal Implications of AI in Surgery
Dr. Hashimoto addresses the ethical and legal considerations regarding the application of AI in surgery. The podcast emphasizes the challenges of data bias, error accountability, and mitigating biases in AI algorithms. The conversation underscores the responsibility of surgeons to critically evaluate AI technologies for patient safety and clinical relevance, emphasizing the importance of ethical data practices and equitable data sources.
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/