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Cited by 169Artificial Intelligence in Healthcare and EducationRadiology practices and educationDiversity and Career in Medicine

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

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

Park, Christian J., Yi, Paul H., Siegel, Eliot L.·2021·Current Problems in Diagnostic Radiology
DOI 10.1067/j.cpradiol.2020.06.011
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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.

Overview

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Crossref · 10.1067/j.cpradiol.2020.06.011

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Metadata

Authors
Park, C. J., Yi, P. H., & Siegel, E. L.
Affiliations
  • Pennsylvania State University (US)
  • Johns Hopkins University (US)
  • University of Maryland Medical Center (US)
Corresponding author
Park, Christian J.
ORCID
Venue
Current Problems in Diagnostic Radiology
Publisher
Elsevier BV
Published
2021-09
Volume
50
Issue
5
Pages
614-619
ISSN
0363-0188 (ISSN-L)
DOI
10.1067/j.cpradiol.2020.06.011
OpenAlex
W3037873741
Cited by
167
References
6
Citations by year
2026: 27 · 2025: 35 · 2024: 24 · 2023: 33 · 2022: 20 · 2021: 24
FWCI
5.81
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Current Problems in Diagnostic Radiology (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiology practices and education
  • Social Sciences › Gender Studies › Diversity and Career in Medicine
Keywords
artificial intelligence, medical students, perceptions of AI, radiology workforce, specialty choice, artificial intelligence in education, misinformation
MeSH terms
Radiologists, Artificial Intelligence, Humans, Radiography, Radiology, Students, Medical, United States

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