The Role of Artificial Intelligence in Surgery: What do General Surgery Residents Think?

Abstract

Background Artificial intelligence (AI) holds significant potential in medical education and patient care, but its rapid emergence presents ethical and practical challenges. This study explored the perspectives of surgical residents on AI's role in medicine. Methods We performed a cross-sectional study surveying general surgery residents at a university-affiliated teaching hospital about their views on AI in medicine and surgical training. The survey covered demographics, residents' understanding of AI, its integration into medical practice, and use of AI tools like ChatGPT. The survey design was inspired by a recent national survey and underwent pretesting before deployment. Results Of the 31 participants surveyed, 24% identified diagnostics as AI's top application, 12% favored its use in identifying anatomical structures in surgeries, and 20% endorsed AI integration into EMRs for predictive models. Attitudes toward AI varied based on its intended application: 77.41% expressed concern about AI making life decisions and 70.97% felt excited about its application for repetitive tasks. A significant 67.74% believed AI could enhance the understanding of medical knowledge. Perception of AI integration varied with AI familiarity ( P = .01), with more knowledgeable respondents expressing more positivity. Moreover, familiarity influenced the perceived academic use of ChatGPT ( P = .039) and attitudes toward AI in operating rooms ( P = .032). Conclusion: This study provides insights into surgery residents’ perceptions of AI in medical practice and training. These findings can inform future research, shape policy decisions, and guide AI development, promoting a harmonious collaboration between AI and surgeons to improve both training and patient care.

Artificial Intelligence and ChatGPT in Abdominopelvic Surgery: A Systematic Review of Applications and Impact

“…Of the included studies, eight were about the capability of the system to generate data output (50%) (3,(5)(6)(7)(8)(9); three (24.4%) considered the decision-making accuracy during tumour board (10) or emergency/intraoperative setting; two (14.2%) about the response quality perception by both medical students and patients (11)(12)(13)(14); One (7%) included the ability of data collection and one (7%) data generation (15,16) (Table I).…”

“…In the second case, on the other hand, opinions were more heterogeneous and not always positive. The authors identified negative opinions especially in patients with a lower level of education (13,14,19). Another aspect of using ChatGPT as a revolutionary support tool for the medical profession is that of decisionmaking support.…”