Elsevier

Current Problems in Diagnostic Radiology

Volume 50, Issue 5, September–October 2021, Pages 614-619
Current Problems in Diagnostic Radiology

Medical Student Perspectives on the Impact of Artificial Intelligence on the Practice of Medicine

https://doi.org/10.1067/j.cpradiol.2020.06.011Get rights and content

Abstract

Introduction

Concerns about radiologists being replaced by artificial intelligence (AI) from the lay media could have a negative impact on medical students’ perceptions of radiology as a viable specialty. The purpose of this study was to evaluate United States of America medical students’ perceptions about radiology and other medical specialties in relation to AI.

Methods

An anonymous, web-based survey was sent to 32 radiology interest groups at United States medical schools. The survey was comprised of 6 questions assessing medical student perceptions of AI and its potential impact on radiology and other medical specialties. Responses were voluntary and collected over a 6-month period from November 2017 to April 2018.

Results

A total of 156 students responded with representation from each year of medical school. Over 75% agreed that AI would have a significant role in the future of medicine. Most (66%) agreed that diagnostic radiology would be the specialty most greatly affected. Nearly half (44%) reported that AI made them less enthusiastic about radiology. The majority of students (57%) obtained their information about AI from online articles. Thematic analysis of free answer comments revealed mostly neutral comments towards AI, however, the negative responses were the strongest and most detailed.

Conclusions

US medical students believe that AI will play a significant role in medicine, particularly in radiology. However, nearly half are less enthusiastic about the field of radiology due to AI. As the majority receive information about AI from online articles, which may have negative sentiments towards AI's impact on radiology, formal AI education and medical student outreach may help combat misinformation and help prevent the dissuading of medical students who might otherwise consider the specialty.

Introduction

Interest and research in artificial Intelligence (AI) has increased dramatically over the last decade1 with billions of dollars projected to be spent towards Deep Learning (DL), in particular.2 As DL has become increasingly applied to medical image analysis, prominent computer scientists have made ominous predictions about the future of radiology, ranging from DL algorithms being able to outperform radiologists in image interpretation4 to calls to “stop training radiologists now.”3 Such sentiments have unsurprisingly been covered heavily by the lay media, both within medical and technology nches4 and more broadly in mainstream outlets.5

Such negative assessments of the future of radiology in relation to AI and DL might be expected to cause medical students to have an unfavorable view of the future of radiology as a specialty to enter. In fact, studies performed in Canada and Europe have shown that AI may be significantly impacting the way that medical students approach their choice of specialty in a negative manner.6,7 In response, a recent editorial has proposed that radiology educators should proactively address these concerns and view AI and DL as an opportunity recruit medical students to a field that will interface intimately and collaboratively with these exciting technologies.

Although the perceptions of medical students towards radiology in relation to AI have been evaluated in both Canada and Europe,6,7 no such study has been performed in the United States. The purpose of this study was thus to evaluate the perceptions of medical students about radiology and other medical specialties in relation to AI.

Section snippets

Survey Administration & Participants

We conducted a survey of medical students in the United States from November 2017 to April of 2018 titled “Artificial Intelligence and the Future of Medicine,” with the goal of evaluating perceptions towards radiology and other medical specialties in relation to AI. We sent our survey in the form of a browser-based, anonymous questionnaire (SurveyMonkey.com, North America) to 32 radiology interest groups at medical schools across the United States chosen to provide a representative mix of

Survey Respondent Summary

There was a total of 156 responses with a very high survey completion rate of 95.4% (of all students who started the survey). There was representation from students from each year (M1: 25.8%, M2: 27.1%, M3:17.4%, M4:29.7%) of medical school (Fig 3).

The effect of AI on the Practice of Medicine During their Career

Over 75% of students revealed that they believed AI would have a moderate-to-major effect on medicine during their careers (Fig 4). A small minority (1.9%) reported that AI would play no part in the future of medicine. On sub-analysis by medical

Discussion

Due to anecdotal reports of medical student concerns regarding AI's influence on the future practice of medicine, as well as sentiments from both medical professionals and the lay media predicting deleterious effects of AI on the viability of diagnostic radiology, we investigated whether there could be a negative impact of AI on medical students’ perceptions of the field. Although medical student perceptions of AI's impact on radiology have been studied in Canada and Europe,6,7 no similar study

Conclusion

The continued misperception of AI as a replacement for radiologists is much more of a threat than the development and integration of AI into the practice of diagnostic imaging, as our study suggests that it may erode medical student enthusiasm for the field. This has to potential to reduce incoming talent into the field and ultimately result in a “brain drain.” Radiology has always been at the forefront of technology utilization and education in medicine – MRI, CT, and picture archiving and

Appendix

List of Contacted Radiology Interest Groups

  • Boston University School of Medicine

  • University of Pennsylvania Perelman School of Medicine

  • University of Alabama Birmingham School of Medicine

  • University of Washington School of Medicine

  • Howard University College of Medicine

  • University of Arkansas for Medical Sciences College of Medicine

  • University of Michigan Medical School

  • Wayne State University School of Medicine

  • University of Arizona College of Medicine

  • Wake Forest School of Medicine

  • University of Maryland

References (8)

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Conflict of Interest: None.

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