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 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.

Artificial intelligence in radiology: does it impact medical students preference for radiology as their future career?

“… 14 In Sit et al study, about half of their students obtained AI-related education, and students who did not obtain such education were significantly less likely to consider radiology as a career. 20 …”

“… 9,14–18 Misunderstanding about the effect of AI on radiology may discourage medical students from considering radiology as a specialty. 14 Previous studies in the same subject from Canada, 14 Germany, 19 UK 20 , and Brazil 21 concluded that AI played a negative role in medical students’ choice for radiology.…”

La inteligencia artificial en la educación médica y la predicción en salud

“…La expansión de la IA en la práctica médica ha generado debates sobre su aplicación en el área de la educación médica en las universidades. En el Reino Unido (UK), el uso de nuevos métodos digitales en salud ha sido objeto de un reciente gobierno nacional 30 . Topol explica con mucho énfasis explícito la importancia de las herramientas digitales novedosas en la enseñanza de pregrado y posgrado con el objetivo de ayudar a las futuras generaciones de estudiantes de medicina en su actividad clínica, incluidos los apoyados por la IA.…”

US primary care in 2029: A Delphi survey on the impact of machine learning

“…Recently a number of surveys have explored medical students', and physicians' views about the impact of AI/ML on the future of medical practice [10][11][12][13][14][15][16]. Currently, there is scarce exploration of consensus views among informaticians [17]; in particular, on how AI/ML might meaningfully influence medical care in the short-term [18].…”