Hakami Khalid M, Alameer Mohammed, Jaawna Essa, Sudi Abdulrahman, Bahkali Bahiyyah, Mohammed Amnah, Hakami Abdulaziz, Mahfouz Mohamed Salih, Alhazmi Abdulaziz H, Dhayihi Turki M
Faculty of Medicine, Jazan University, Jazan, SAU.
Faculty of Medicine, Jazan University, jazan, SAU.
Cureus. 2023 Jul 13;15(7):e41840. doi: 10.7759/cureus.41840. eCollection 2023 Jul.
Background The use of artificial intelligence (AI) in healthcare continues to spark interest and has been the subject of extensive discussion in recent years as well as its potential effects on future medical specialties, including radiology. In this study, we aimed to study the impact of AI on the preference of medical students at Jazan University in choosing radiology as a future specialty. Methodology An observational cross-sectional study was conducted using a pre-tested self-administered online questionnaire among medical students at Jazan University. Data were cleaned, coded, entered, and analyzed using SPSS (SPSS Inc., USA) version 25. Statistical significance was defined as a P-value of less than 0.05. We examined the respondents' preference for radiology rankings with the presence and absence of AI. Radiology's ranking as a preferred specialty with or without AI integration was statistically analyzed for associations with baseline characteristics, personal opinions, and previous exposures among those who had radiology as one of their top three options. Results Approximately 27.4% of males and 28.3% of females ranked radiology among their top three preferred choices. Almost 65.2% were exposed to radiology topics through pre-clinical lectures. The main sources of information about AI for the studied group were medical students (41%) and the Internet (27.5%). The preference of students for radiology was significantly affected when it is assessed by AI (P < 0.05). Around (16.1%) of those who chose radiology as one of their top three choices strongly agree that AI will decrease the job opportunities for radiologists. Logistic regression analysis showed that being a female is significantly associated with an increased chance to replace radiology with other specialty when it is integrated with AI (Crude odds ratio (COR) = 1.91). Conclusion Our results demonstrated that the students' choices were significantly affected by the presence of AI. Thereover, to raise medical students' knowledge and awareness of the potential positive effects of AI, it is necessary to organize an educational campaign, webinars, and conferences.
背景 人工智能（AI）在医疗保健领域的应用持续引发关注，近年来一直是广泛讨论的主题，以及其对包括放射学在内的未来医学专业的潜在影响。在本研究中，我们旨在研究人工智能对吉赞大学医学生选择放射学作为未来专业偏好的影响。方法 使用预先测试的自填式在线问卷对吉赞大学的医学生进行观察性横断面研究。数据使用SPSS（美国SPSS公司）25版进行清理、编码、录入和分析。统计学显著性定义为P值小于0.05。我们研究了有和没有人工智能情况下受访者对放射学排名的偏好。对将放射学作为前三个选择之一的人群中，有或没有人工智能整合时放射学作为首选专业的排名进行统计学分析，以探讨与基线特征、个人意见和既往接触情况的关联。结果 约27.4%的男性和28.3%的女性将放射学列为前三个首选专业之一。近65.2%的人通过临床前讲座接触过放射学主题。研究组获取人工智能信息的主要来源是医学生（41%）和互联网（27.5%）。当通过人工智能评估时，学生对放射学的偏好受到显著影响（P < 0.05）。在将放射学作为前三个选择之一的人中，约16.1%的人强烈同意人工智能将减少放射科医生的就业机会。逻辑回归分析表明，女性与在放射学与人工智能整合时用其他专业替代放射学的机会增加显著相关（粗比值比（COR）= 1.91）。结论 我们的结果表明，人工智能的存在显著影响了学生的选择。此外，为提高医学生对人工智能潜在积极影响的知识和认识，有必要组织教育活动、网络研讨会和会议。
