Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Gyeonggi-do, Republic of Korea.
Center for Digital Health, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Gyeonggi-do, Republic of Korea.
PLoS One. 2023 Mar 2;18(3):e0282123. doi: 10.1371/journal.pone.0282123. eCollection 2023.
To assess experience with and perceptions of clinical application of artificial intelligence (AI) to chest radiographs among doctors in a single hospital.
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.
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.
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.
评估单家医院医生对胸部 X 光片人工智能（AI）临床应用的经验和看法。
在这项前瞻性研究中，我们对医院内所有临床医生和放射科医生进行了一项关于使用商业 AI 基于病灶检测软件进行胸部 X 光片的全院范围在线调查。在我院，上述软件的 2 版本于 2020 年 3 月至 2021 年 2 月期间使用，可检测三种类型的病灶。自 2021 年 3 月起，3 版本开始用于检测九种类型的病灶。参与这项调查的人员回答了他们在日常实践中使用 AI 软件的经验相关问题。调查问卷由单项选择、多项选择和量表问题组成。根据临床医生和放射科医生使用配对 t 检验和 Wilcoxon 秩和检验对答案进行分析。
共有 123 名医生回答了调查，其中 74%的人完成了所有问题。放射科医生使用 AI 的比例高于临床医生（82.5%比 45.9%，p = 0.008）。AI 在急诊室被认为最有用，气胸被认为是最有价值的发现。大约 21%的临床医生和 16%的放射科医生在参考 AI 后改变了自己的阅读结果，对 AI 的信任度分别为 64.9%和 66.5%。参与者认为 AI 有助于减少阅读时间和阅读请求。他们回答 AI 有助于提高诊断准确性，在实际使用 AI 后对 AI 更加肯定。
在这项全院范围内的调查中，实际应用 AI 进行日常胸部 X 光片检查得到了临床医生和放射科医生的总体积极反馈。参与调查的医生更喜欢使用 AI，并且在实际使用基于 AI 的软件进行日常临床实践后，对 AI 的评价更为积极。
