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Hospital-wide survey of clinical experience with artificial intelligence applied to daily chest radiographs

Authors
 Shin, Hyun Joo  ;  Lee, Seungsoo  ;  Kim, Sungwon  ;  Son, Nak-Hoon  ;  Kim, Eun Kyung 
Citation
 PLoS ONE, Vol.18(3), 2023-03 
Article Number
 e0282123 
Journal Title
PLOS ONE
ISSN
 1932-6203 
Issue Date
2023-03
Abstract
PurposeTo assess experience with and perceptions of clinical application of artificial intelligence (AI) to chest radiographs among doctors in a single hospital. Materials and methodsA hospital-wide online survey of the use of commercially available AI-based lesion detection software for chest radiographs was conducted with all clinicians and radiologists at our hospital in this prospective study. In our hospital, version 2 of the abovementioned software was utilized from March 2020 to February 2021 and could detect three types of lesions. Version 3 was utilized for chest radiographs by detecting nine types of lesions from March 2021. The participants of this survey answered questions on their own experience using AI-based software in daily practice. The questionnaires were composed of single choice, multiple choices, and scale bar questions. Answers were analyzed according to the clinicians and radiologists using paired t-test and the Wilcoxon rank-sum test. ResultsOne hundred twenty-three doctors answered the survey, and 74% completed all questions. The proportion of individuals who utilized AI was higher among radiologists than clinicians (82.5% vs. 45.9%, p = 0.008). AI was perceived as being the most useful in the emergency room, and pneumothorax was considered the most valuable finding. Approximately 21% of clinicians and 16% of radiologists changed their own reading results after referring to AI, and trust levels for AI were 64.9% and 66.5%, respectively. Participants thought AI helped reduce reading times and reading requests. They answered that AI helped increase diagnostic accuracy and were more positive about AI after actual usage. ConclusionActual adaptation of AI for daily chest radiographs received overall positive feedback from clinicians and radiologists in this hospital-wide survey. Participating doctors preferred to use AI and regarded it more favorably after actual working with the AI-based software in daily clinical practice.
DOI
10.1371/journal.pone.0282123
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Sungwon(김성원)
Kim, Eun-Kyung(김은경) ORCID logo https://orcid.org/0000-0002-3368-5013
Shin, Hyun Joo(신현주) ORCID logo https://orcid.org/0000-0002-7462-2609
Lee, Seung Soo(이승수) ORCID logo https://orcid.org/0000-0002-6268-575X
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/193757
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