Townsville University Hospital, 100 Angus Smith Drive, Douglas, Townsville, QLD, Australia.
Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
Clin Imaging. 2021 Dec;80:413-419. doi: 10.1016/j.clinimag.2021.08.004. Epub 2021 Aug 14.
There exists many single sample perspectives on artificial intelligence (AI). The aim of this review was to collate the current data on attitudes/knowledge towards AI in three unique populations: medical students, clinicians and patients.
A literature search was performed on PubMed, Scopus and Web of Science pertaining to survey data on AI in radiology. Quality assessment was performed by an adapted version of the assessment tool from the National Heart, Lung and Blood Institute for Observational Studies.
Fourteen studies were found on attitudes/knowledge towards AI in radiology. Four studies examined medical students, seven on clinicians and three on patient populations. Deficiencies in the literature mainly related to sampling bias. Students had anxiety relating to future job prospects. Clinicians were optimistic and viewed AI as an aid to the diagnosis and wanted to further their knowledge. Patients were concerned about the lack of human interaction and accountability during error.
Attitudes and knowledge regarding AI in radiology remains a topic that needs to be researched further and education given pertaining to its use in a clinical setting.
目前已有许多针对人工智能（AI）的单一样本观点。本综述旨在综合目前关于三个独特群体（医学生、临床医生和患者）对 AI 的态度/知识的现有数据。
在 PubMed、Scopus 和 Web of Science 上对与放射科 AI 相关的调查数据进行了文献检索。使用国家心肺血液研究所的观察研究评估工具的改编版本进行质量评估。
共发现了 14 项关于放射科 AI 的态度/知识的研究。其中 4 项研究针对医学生，7 项针对临床医生，3 项针对患者群体。文献中的缺陷主要与抽样偏差有关。学生对未来的工作前景感到焦虑。临床医生持乐观态度，并将 AI 视为诊断的辅助手段，希望进一步了解其知识。患者担心在出现错误时缺乏人机交互和问责制。
放射科 AI 的态度和知识仍然是一个需要进一步研究的课题，并需要就其在临床环境中的使用进行教育。
