Your browser doesn't support javascript.
loading
Knowledge, attitude, and perception of Arab medical students towards artificial intelligence in medicine and radiology: A multi-national cross-sectional study.
Allam, Ahmed Hafez; Eltewacy, Nael Kamel; Alabdallat, Yasmeen Jamal; Owais, Tarek A; Salman, Saif; Ebada, Mahmoud A.
Afiliación
  • Allam AH; Faculty of Medicine, Menoufia University, Shebin El-Kom, Menoufia, Egypt. ahmedhafez21@med.menofia.edu.eg.
  • Eltewacy NK; Eltewacy Arab Research Group, Cairo, Egypt. ahmedhafez21@med.menofia.edu.eg.
  • Alabdallat YJ; Eltewacy Arab Research Group, Cairo, Egypt.
  • Owais TA; Faculty of Pharmacy, Beni-Suef University, Beni-Suef, Egypt.
  • Salman S; Eltewacy Arab Research Group, Cairo, Egypt.
  • Ebada MA; Faculty of Medicine, Hashemite University, Zarqa, Jordan.
Eur Radiol ; 34(7): 1-14, 2024 Jul.
Article en En | MEDLINE | ID: mdl-38150076
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.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Radiología / Estudiantes de Medicina / Inteligencia Artificial / Conocimientos, Actitudes y Práctica en Salud Límite: Adult / Female / Humans / Male País/Región como asunto: Asia Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Egipto

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Radiología / Estudiantes de Medicina / Inteligencia Artificial / Conocimientos, Actitudes y Práctica en Salud Límite: Adult / Female / Humans / Male País/Región como asunto: Asia Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Egipto