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The Impact of Emerging Technologies on Residency Selection by Medical Students in 2017 and 2021, With a Focus on Diagnostic Radiology

  • Michael K. Atalay
    Correspondence
    Address correspondence to: M.K.A.
    Affiliations
    Department of Diagnostic Imaging (M.K.A., G.L.B., M.T.S., K.O., J.J.C.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, 593 Eddy Street, Providence, RI 02903

    Radiology Human Factors Laboratory, Department of Diagnostic Imaging (M.K.A., G.L.B.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, Providence, Rhode Island
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  • Grayson L. Baird
    Affiliations
    Department of Diagnostic Imaging (M.K.A., G.L.B., M.T.S., K.O., J.J.C.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, 593 Eddy Street, Providence, RI 02903

    Radiology Human Factors Laboratory, Department of Diagnostic Imaging (M.K.A., G.L.B.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, Providence, Rhode Island
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  • Matthew T. Stib
    Affiliations
    Department of Diagnostic Imaging (M.K.A., G.L.B., M.T.S., K.O., J.J.C.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, 593 Eddy Street, Providence, RI 02903
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  • Paul George
    Affiliations
    Office of Medical Education (P.G.), Warren Alpert School of Medicine of Brown University, Providence, Rhode Island
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  • Karim Oueidat
    Affiliations
    Department of Diagnostic Imaging (M.K.A., G.L.B., M.T.S., K.O., J.J.C.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, 593 Eddy Street, Providence, RI 02903
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  • John J. Cronan
    Affiliations
    Department of Diagnostic Imaging (M.K.A., G.L.B., M.T.S., K.O., J.J.C.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, 593 Eddy Street, Providence, RI 02903
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Published:September 01, 2022DOI:https://doi.org/10.1016/j.acra.2022.07.003

      Rationale and Objectives

      We sought to determine the perceived impact of artificial intelligence (AI) and other emerging technologies (ET) on various specialties by medical students in both 2017 and 2021 and how this might affect their residency selections.

      Materials and Methods

      We conducted a brief, anonymous survey of all medical students at a single institution in 2017 and 2021. Survey questions evaluated (1) incentives motivating residency selection and career path, (2) degree of interest in each specialty, (3) perceived effect that ET will have on job prospects for each specialty, and (4) those specialties that students would not consider because of concerns regarding ET.

      Results

      A total of 72% (384/532) and 54% (321/598) of medical students participated in the survey in 2017 and 2021, respectively, and results were largely stable. Students perceived ET would reduce job prospects for pathology, diagnostic radiology, and anesthesiology, and enhance prospects for all other specialties (p < 0.01) except dermatology. For both surveys, 23% of students would NOT consider diagnostic radiology because ET would make it obsolete, higher than all other specialties (p < 0.01). Regarding the one student class that was surveyed twice, 50% felt ET would reduce job prospects for radiology in 2017, increasing to 71% in 2021 (p < 0.01), and similar percentages—20% in 2017 and 23% in 2021—said they explicitly would not consider radiology because of concerns levied by ET.

      Conclusions

      Current perceptions of ET likely affect residency selection for a large proportion of medical students and may impact the future of various specialties, particularly diagnostic radiology.

      Key Words

      Abbreviations:

      AI (artificial intelligence), ET (emerging technology)
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