Faculty of Medicine, Menoufia University, Shebin El-Kom, Menoufia, Egypt.
Eltewacy Arab Research Group, Cairo, Egypt.
Eur Radiol. 2024 Jul;34(7):1-14. doi: 10.1007/s00330-023-10509-2. Epub 2023 Dec 27.
We aimed to assess undergraduate medical students' knowledge, attitude, and perception regarding artificial intelligence (AI) in medicine.
A multi-national, multi-center cross-sectional study was conducted from March to April 2022, targeting undergraduate medical students in nine Arab countries. The study utilized a web-based questionnaire, with data collection carried out with the help of national leaders and local collaborators. Logistic regression analysis was performed to identify predictors of knowledge, attitude, and perception among the participants. Additionally, cluster analysis was employed to identify shared patterns within their responses.
Of the 4492 students surveyed, 92.4% had not received formal AI training. Regarding AI and deep learning (DL), 87.1% exhibited a low level of knowledge. Most students (84.9%) believed AI would revolutionize medicine and radiology, with 48.9% agreeing that it could reduce the need for radiologists. Students with high/moderate AI knowledge and training had higher odds of agreeing to endorse AI replacing radiologists, reducing their numbers, and being less likely to consider radiology as a career compared to those with low knowledge/no AI training. Additionally, the majority agreed that AI would aid in the automated detection and diagnosis of pathologies.
Arab medical students exhibit a notable deficit in their knowledge and training pertaining to AI. Despite this, they hold a positive perception of AI implementation in medicine and radiology, demonstrating a clear understanding of its significance for the healthcare system and medical curriculum.
This study highlights the need for widespread education and training in artificial intelligence for Arab medical students, indicating its significance for healthcare systems and medical curricula.
• Arab medical students demonstrate a significant knowledge and training gap when it comes to using AI in the fields of medicine and radiology. • Arab medical students recognize the importance of integrating AI into the medical curriculum. Students with a deeper understanding of AI were more likely to agree that all medical students should receive AI education. However, those with previous AI training were less supportive of this idea. • Students with moderate/high AI knowledge and training displayed increased odds of agreeing that AI has the potential to replace radiologists, reduce the demand for their services, and were less inclined to pursue a career in radiology, when compared to students with low knowledge/no AI training.
评估医学生对人工智能(AI)在医学中的知识、态度和看法。
本研究为多国多中心的横断面研究,于 2022 年 3 月至 4 月期间开展,对象为 9 个阿拉伯国家的医学生。研究采用基于网络的问卷,在国家领导人和当地合作者的帮助下收集数据。采用逻辑回归分析识别参与者知识、态度和看法的预测因素。此外,采用聚类分析识别其反应中的共同模式。
在接受调查的 4492 名学生中,92.4%未接受过 AI 培训。在 AI 和深度学习(DL)方面,87.1%的学生知识水平较低。大多数学生(84.9%)认为 AI 将彻底改变医学和放射学,48.9%的学生认为 AI 可以减少放射科医生的需求。与知识水平低/未接受 AI 培训的学生相比,AI 知识和培训水平较高的学生更有可能同意 AI 取代放射科医生、减少放射科医生数量,并认为放射科不是一个好的职业选择。此外,大多数学生同意 AI 将有助于病理的自动检测和诊断。
阿拉伯医学生在 AI 知识和培训方面存在明显不足。尽管如此,他们对 AI 在医学和放射学中的应用持有积极的看法,清楚地认识到 AI 对医疗保健系统和医学课程的重要性。
本研究强调了为阿拉伯医学生提供人工智能广泛教育和培训的必要性,这表明其对医疗保健系统和医学课程的重要性。
阿拉伯医学生在医学和放射学领域使用 AI 方面表现出显著的知识和培训差距。
阿拉伯医学生认识到将 AI 纳入医学课程的重要性。对 AI 有更深入了解的学生更有可能同意所有医学生都应该接受 AI 教育,但那些有 AI 培训背景的学生则不太支持这一观点。
与知识水平低/未接受 AI 培训的学生相比,AI 知识和培训水平较高的学生更有可能同意 AI 有可能取代放射科医生、减少对其服务的需求,并且不太倾向于从事放射科职业。