Knowledge, attitude, and perception of Arab medical students towards artificial intelligence in medicine and radiology: A multi-national cross-sectional study

Author:

Allam Ahmed HafezORCID,Eltewacy Nael Kamel,Alabdallat Yasmeen Jamal,Owais Tarek A.,Salman Saif,Ebada Mahmoud A.,Aldare Hajar Alkokhiya,Rais Mohammed Amir,Salem Moath,Al-Dabagh Jaafar D.,Alhassan Monzer Abdulatif,Hanjul Marah M.,Mugibel Tayba Abdulrahman,Motawea Sara Hamada,Hussein Mirna,Anas Omar Saeed,Amine Nacer Mohamed,Almekhlafi Moath Ahmed,Mugibel Muna Ali,Barhoom Eman Salem,Neiroukh Haroun,Shweiki Raghad,Balaw Mohammad Khalaf,Al-Slehat Mohmmad Ahmad,Roze Zaynab,Sadeq Maram A.,Mokhtar Fathia,Babiker Noora Mahdi,Al-Ati Rami Abd,Alhoudairi Huda Adel,Attayeb Mohammed Omran,Abdulhadi Abdulrhman,Arja Abdulghani,Wardeh Abdulkareem Muhammad,Alakhrass Dana Nabil,Alkanj Souad,

Abstract

Abstract Objectives We aimed to assess undergraduate medical students’ knowledge, attitude, and perception regarding artificial intelligence (AI) in medicine. Methods 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. Results 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. Conclusions 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. Clinical relevance statement 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. Key Points 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.

Funder

The Science, Technology & Innovation Funding Authority

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3