Medical Students’ Knowledge and Attitude Towards Artificial Intelligence: An Online Survey
Mouna M. Al Saad1, *, Amin Shehadeh2, Salem Alanazi3, Monerah Alenezi3, Ahmad Abu alez3, Hana Eid3, Mohammed Saif Alfaouri3, Sultan Aldawsari3, Rawan Alenezi3
Identifiers and Pagination:Year: 2022
E-location ID: e187494452203290
Publisher ID: e187494452203290
Article History:Received Date: 10/12/2021
Revision Received Date: 14/1/2022
Acceptance Date: 27/1/2022
Electronic publication date: 24/05/2022
Collection year: 2022
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Within the near future, doctors can be anticipated to encounter patients in very distinctive wellbeing care settings compared with the present time. As a result, artificial intelligence will be an essential tool.
The purpose of this study is to investigate the attitudes of Jordanian medical students regarding Artificial Intelligence (AI) and Machine Learning (ML). Moreover, to estimate the level of knowledge and understanding of the effects of AI on medical students.
Nine hundred medical students from six universities in Jordan participated in this survey. The participants were asked to fill out an electronic pre-validated questionnaire using Google’s forms and those forms were published via social media. The questionnaire included questions of Likert and dichotomous questions.
89% of the students believed in the importance of AI in the medical field, and 71.4% believed in the beneficiary of teaching AI in the medical career. 47% of the students had an understanding of the basic principles of AI, 68.4% of the students believed that it is mandatory for medical students to receive knowledge of AI. Statistically, students who received teaching/training in AI were more likely to consider radiology as a career given the advancement in AI (p = 0.000).
Medical students in Jordanian universities appreciate the importance of artificial intelligence and machine learning in medical advancements. Adding courses and training related to artificial intelligence and machine learning to the study plan should be considered.