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01-01-2021 | Artificial Intelligence | COMPUTER APPLICATION

Artificial intelligence: radiologists’ expectations and opinions gleaned from a nationwide online survey

Authors: Francesca Coppola, Lorenzo Faggioni, Daniele Regge, Andrea Giovagnoni, Rita Golfieri, Corrado Bibbolino, Vittorio Miele, Emanuele Neri, Roberto Grassi

Published in: La radiologia medica | Issue 1/2021

Abstract

Purpose

To report the results of a nationwide online survey on artificial intelligence (AI) among radiologist members of the Italian Society of Medical and Interventional Radiology (SIRM).

Methods and materials

All members were invited to the survey as an initiative by the Imaging Informatics Chapter of SIRM. The survey consisted of 13 questions about the participants’ demographic information, perceived advantages and issues related to AI implementation in radiological practice, and their overall opinion about AI.

Results

In total, 1032 radiologists (equaling 9.5% of active SIRM members for the year 2019) joined the survey. Perceived AI advantages included a lower diagnostic error rate (750/1027, 73.0%) and optimization of radiologists’ work (697/1027, 67.9%). The risk of a poorer professional reputation of radiologists compared with non-radiologists (617/1024, 60.3%), and increased costs and workload due to AI system maintenance and data analysis (399/1024, 39.0%) were seen as potential issues. Most radiologists stated that specific policies should regulate the use of AI (933/1032, 90.4%) and were not afraid of losing their job due to it (917/1032, 88.9%). Overall, 77.0% of respondents (794/1032) were favorable to the adoption of AI, whereas 18.0% (186/1032) were uncertain and 5.0% (52/1032) were unfavorable.

Conclusions

Radiologists had a mostly positive attitude toward the implementation of AI in their working practice. They were not concerned that AI will replace them, but rather that it might diminish their professional reputation.

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Title: Artificial intelligence: radiologists’ expectations and opinions gleaned from a nationwide online survey
Authors: Francesca Coppola
Lorenzo Faggioni
Daniele Regge
Andrea Giovagnoni
Rita Golfieri
Corrado Bibbolino
Vittorio Miele
Emanuele Neri
Roberto Grassi
Publication date: 01-01-2021
Publisher: Springer Milan
Keyword: Artificial Intelligence
Published in: La radiologia medica / Issue 1/2021
Print ISSN: 0033-8362
Electronic ISSN: 1826-6983
DOI: https://doi.org/10.1007/s11547-020-01205-y

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Artificial intelligence: radiologists’ expectations and opinions gleaned from a nationwide online survey

Abstract

Purpose

Methods and materials

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Methods and materials

Results

Conclusions

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