Bisdas, Sotirios;
Topriceanu, Constantin-Cristian;
Zakrzewska, Zosia;
Irimia, Alexandra-Valentina;
Shakallis, Loizos;
Subhash, Jithu;
Casapu, Maria-Madalina;
... Ebrahim, Esraa Hasan; + view all
(2021)
Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students' Perception.
Frontiers in Public Health
, 9
, Article 795284. 10.3389/fpubh.2021.795284.
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Abstract
Background: The emerging field of artificial intelligence (AI) will probably affect the practice for the next generation of doctors. However, the students' views on AI have not been largely investigated. Methods: An anonymous electronic survey on AI was designed for medical and dental students to explore: (1) sources of information about AI, (2) AI applications and concerns, (3) AI status as a topic in medicine, and (4) students' feelings and attitudes. The questionnaire was advertised on social media platforms in 2020. Security measures were employed to prevent fraudulent responses. Mann-Whitney U-test was employed for all comparisons. A sensitivity analysis was also performed by binarizing responses to express disagreement and agreement using the Chi-squared test. Results: Three thousand one hundred thirty-three respondents from 63 countries from all continents were included. Most respondents reported having at least a moderate understanding of the technologies underpinning AI and of their current application, with higher agreement associated with being male (p < 0.0001), tech-savvy (p < 0.0001), pre-clinical student (p < 0.006), and from a developed country (p < 0.04). Students perceive AI as a partner rather than a competitor (72.2%) with a higher agreement for medical students (p = 0.002). The belief that AI will revolutionize medicine and dentistry (83.9%) with greater agreement for students from a developed country (p = 0.0004) was noted. Most students agree that the AI developments will make medicine and dentistry more exciting (69.9%), that AI shall be part of the medical training (85.6%) and they are eager to incorporate AI in their future practice (99%). Conclusion: Currently, AI is a hot topic in medicine and dentistry. Students have a basic understanding of AI principles, a positive attitude toward AI and would like to have it incorporated into their training.
| Type: | Article |
|---|---|
| Title: | Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students' Perception |
| Location: | Switzerland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fpubh.2021.795284 |
| Publisher version: | https://doi.org/10.3389/fpubh.2021.795284 |
| Language: | English |
| Additional information: | Copyright © 2021 Bisdas, Topriceanu, Zakrzewska, Irimia, Shakallis, Subhash, Casapu, Leon-Rojas, Pinto dos Santos, Andrews, Zeicu, Bouhuwaish, Lestari, Abu-Ismail, Sadiq, Khamees, Mohammed, Williams, Omran, Ismail and Ebrahim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Public, Environmental & Occupational Health, artificial intelligence, dental students, medical students, medicine, survey, FUTURE, MODEL |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10162911 |
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