Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey

Abstract Objectives To explore the attitudes of United Kingdom (UK) medical students regarding artificial intelligence (AI), their understanding, and career intention towards radiology. We also examine the state of education relating to AI amongst this cohort. Methods UK medical students were invite...

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Main Authors: Cherry Sit, Rohit Srinivasan, Ashik Amlani, Keerthini Muthuswamy, Aishah Azam, Leo Monzon, Daniel Stephen Poon
Format: Article
Language:English
Published: SpringerOpen 2020-02-01
Series:Insights into Imaging
Subjects:
Online Access:https://doi.org/10.1186/s13244-019-0830-7
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spelling doaj-c802385de9c64867b602d2cd6a7e02592021-02-07T12:25:37ZengSpringerOpenInsights into Imaging1869-41012020-02-011111610.1186/s13244-019-0830-7Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre surveyCherry Sit0Rohit Srinivasan1Ashik Amlani2Keerthini Muthuswamy3Aishah Azam4Leo Monzon5Daniel Stephen Poon6Department of Radiology, Guy’s and St. Thomas’ NHS Foundation TrustDepartment of Radiology, Guy’s and St. Thomas’ NHS Foundation TrustDepartment of Radiology, Guy’s and St. Thomas’ NHS Foundation TrustDepartment of Radiology, Guy’s and St. Thomas’ NHS Foundation TrustDepartment of Radiology, Guy’s and St. Thomas’ NHS Foundation TrustDepartment of Interventional Radiology, Guy’s and St. Thomas’ NHS Foundation TrustDepartment of Radiology, Guy’s and St. Thomas’ NHS Foundation TrustAbstract Objectives To explore the attitudes of United Kingdom (UK) medical students regarding artificial intelligence (AI), their understanding, and career intention towards radiology. We also examine the state of education relating to AI amongst this cohort. Methods UK medical students were invited to complete an anonymous electronic survey consisting of Likert and dichotomous questions. Results Four hundred eighty-four responses were received from 19 UK medical schools. Eighty-eight percent of students believed that AI will play an important role in healthcare, and 49% reported they were less likely to consider a career in radiology due to AI. Eighty-nine percent of students believed that teaching in AI would be beneficial for their careers, and 78% agreed that students should receive training in AI as part of their medical degree. Only 45 students received any teaching on AI; none of the students received such teaching as part of their compulsory curriculum. Statistically, students that did receive teaching in AI were more likely to consider radiology (p = 0.01) and rated more positively to the questions relating to the perceived competence in the post-graduation use of AI (p = 0.01–0.04); despite this, a large proportion of students in the taught group reported a lack of confidence and understanding required for the critical use of healthcare AI tools. Conclusions UK medical students understand the importance of AI and are keen to engage. Medical school training on AI should be expanded and improved. Realistic use cases and limitations of AI must be presented to students so they will not feel discouraged from pursuing radiology.https://doi.org/10.1186/s13244-019-0830-7Artificial intelligenceEducationMedical studentRadiology
collection DOAJ
language English
format Article
sources DOAJ
author Cherry Sit
Rohit Srinivasan
Ashik Amlani
Keerthini Muthuswamy
Aishah Azam
Leo Monzon
Daniel Stephen Poon
spellingShingle Cherry Sit
Rohit Srinivasan
Ashik Amlani
Keerthini Muthuswamy
Aishah Azam
Leo Monzon
Daniel Stephen Poon
Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey
Insights into Imaging
Artificial intelligence
Education
Medical student
Radiology
author_facet Cherry Sit
Rohit Srinivasan
Ashik Amlani
Keerthini Muthuswamy
Aishah Azam
Leo Monzon
Daniel Stephen Poon
author_sort Cherry Sit
title Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey
title_short Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey
title_full Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey
title_fullStr Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey
title_full_unstemmed Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey
title_sort attitudes and perceptions of uk medical students towards artificial intelligence and radiology: a multicentre survey
publisher SpringerOpen
series Insights into Imaging
issn 1869-4101
publishDate 2020-02-01
description Abstract Objectives To explore the attitudes of United Kingdom (UK) medical students regarding artificial intelligence (AI), their understanding, and career intention towards radiology. We also examine the state of education relating to AI amongst this cohort. Methods UK medical students were invited to complete an anonymous electronic survey consisting of Likert and dichotomous questions. Results Four hundred eighty-four responses were received from 19 UK medical schools. Eighty-eight percent of students believed that AI will play an important role in healthcare, and 49% reported they were less likely to consider a career in radiology due to AI. Eighty-nine percent of students believed that teaching in AI would be beneficial for their careers, and 78% agreed that students should receive training in AI as part of their medical degree. Only 45 students received any teaching on AI; none of the students received such teaching as part of their compulsory curriculum. Statistically, students that did receive teaching in AI were more likely to consider radiology (p = 0.01) and rated more positively to the questions relating to the perceived competence in the post-graduation use of AI (p = 0.01–0.04); despite this, a large proportion of students in the taught group reported a lack of confidence and understanding required for the critical use of healthcare AI tools. Conclusions UK medical students understand the importance of AI and are keen to engage. Medical school training on AI should be expanded and improved. Realistic use cases and limitations of AI must be presented to students so they will not feel discouraged from pursuing radiology.
topic Artificial intelligence
Education
Medical student
Radiology
url https://doi.org/10.1186/s13244-019-0830-7
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