Exploring the awareness of artificial intelligence among vascular surgeons in the Middle East

<h2>Abstract</h2><h3>Background</h3> Artificial intelligence (AI) and machine learning (ML) are transforming healthcare, with significant potential to enhance diagnosis, prognosis, and treatment. In vascular surgery, AI/ML has demonstrated promise not only in predicting outcomes and aiding imaging diagnostics but also in optimizing patient selection and procedural planning. However, clinical adoption remains limited, necessitating an understanding of clinician perspectives to identify facilitators and barriers. This study aims to assess the knowledge, attitudes, and perceptions of vascular surgeons in the Middle East regarding AI/ML, identify key barriers and facilitators for adoption, and explore their clinical applicability in vascular surgery. <h3>Methods</h3> A survey was conducted among vascular surgeons practicing in Bahrain, Egypt, Kuwait, Jordan, Oman, Saudi Arabia, Syria, and the United Arab Emirates to assess their demographics, knowledge, attitudes, and perceptions regarding AI/ML.The survey explored self-assessed knowledge, formal training in AI, perceived applications, confidence in integrating AI/ML tools, and concerns regarding errors, bias, and ethical implications. A total of 65 vascular surgeons participated in the survey, with a response rate of 16.5%. <h3>Results</h3> Respondents (median age 41, mean age 43.9) were predominantly male (70%), with 45% having less than 10 years of practice experience. While most (44%) rated their AI/ML knowledge as "fair," 90% reported no formal training in AI, indicating a substantial knowledge gap. Despite this, 74% expressed moderate to high excitement about AI/ML, with 61% believing it could significantly or extremely improve patient outcomes. The primary areas of interest included image analysis, clinical decision support, and patient selection. Concerns centered on errors leading to patient harm (47%), data security/privacy issues (42%), and 67% of clinicians reported moderate to high levels of ethical concern. <h3>Conclusions</h3> Middle Eastern vascular surgeons acknowledge the potential of AI/ML to improve patient care but face significant barriers to adoption, including limited knowledge, training deficits in AI, and ethical concerns. Addressing these challenges through targeted education, transparent AI/ML tools, and ethical oversight is critical for successful integration into clinical practice. These findings highlight the need for tailored strategies to bridge the gap between AI/ML innovation and its practical utility in vascular surgery.