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

 Hyun Joo Shin  ;  Seungsoo Lee  ;  Sungwon Kim  ;  Nak-Hoon Son  ;  Eun-Kyung Kim 
 PLOS ONE, Vol.18(3) : e0282123, 2023-03 
Journal Title
Issue Date
Artificial Intelligence* ; Hospitals ; Humans ; Physicians* ; Prospective Studies ; Software
Purpose: To assess experience with and perceptions of clinical application of artificial intelligence (AI) to chest radiographs among doctors in a single hospital.

Materials and methods: A 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.

Results: One 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.

Conclusion: Actual 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.
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Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Sungwon(김성원) ORCID logo https://orcid.org/0000-0001-5455-6926
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
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