Knowledge, attitude, and perception of Arab
medical students towards artificial intelligence in medicine and radiology: A
multi-national cross-sectional study
Authors: Allam Ahmed Hafez , Eltewacy Nael Kamel , Alabdallat Yasmeen Jamal , Owais Tarek A. , Salman Saif , Ebada Mahmoud A. ,   for the EARG Group, 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 
Published: December 2023

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.