Defining the artificial intelligence knowledge gap in surgery: experience and perspectives from surgical resident and postgraduate.
Researchers
Zhongshang Dai, Zhuoyuan Chen, Liang Weng, Lin Guo, Zhehao Dai
Abstract
Despite the growing prominence of Artificial Intelligence (AI) in surgical practice, surgical residents and postgraduates receive limited formal training. A cross-sectional survey of 322 surgical residents and postgraduates from three Chinese medical universities assessed their knowledge, perceptions, and experience regarding AI in surgical practice. Among respondents, 76.7% reported prior experience with clinical AIrelated applications and generally recognized their value. However, self-reported preparedness to critically appraise AI and use it responsibly was modest or low. In particular, over 75% of respondents expressed limited confidence in evaluating model reliability and in identifying bias or other limitations. 85.7% supported the formal integration of AI into surgical training programs. On the other hand, 267 respondents reported that they had not received any formal AI training. Interest in AI-related topic differed significantly across training stages (χ<sup>2</sup> = 39.12, p < 0.01). Postgraduate year 1 (PGY1) residents were most interested in learning the AI basics. PGY2 residents preferred topics about Human-AI collaboration and AI-assisted imaging analysis. PGY3 residents expressed interest in AI for research design and data analysis. These findings indicate a significant gap in AI education, highlighting the need for a stage-tailored and specialty-aware structured AI curriculum to prepare surgeons for the evolving world of healthcare technology.Source: PubMed (PMID: 42166094)View Original on PubMed