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医学生对机器学习的知识和批判性评价:一项多中心国际横断面研究。

Medical student knowledge and critical appraisal of machine learning: a multicentre international cross-sectional study.

机构信息

University of Adelaide, Adelaide, South Australia, Australia.

Royal Adelaide Hospital, Adelaide, South Australia, Australia.

出版信息

Intern Med J. 2021 Sep;51(9):1539-1542. doi: 10.1111/imj.15479.

Abstract

To utilise effectively tools that employ machine learning (ML) in clinical practice medical students and doctors will require a degree of understanding of ML models. To evaluate current levels of understanding, a formative examination and survey was conducted across three centres in Australia, New Zealand and the United States. Of the 245 individuals who participated in the study (response rate = 45.4%), the majority had difficulty with identifying weaknesses in model performance analysis. Further studies examining educational interventions addressing such ML topics are warranted.

摘要

为了在临床实践中有效地使用机器学习(ML)工具,医学生和医生需要对 ML 模型有一定的理解。为了评估当前的理解水平,在澳大利亚、新西兰和美国的三个中心进行了一次形成性考试和调查。在 245 名参与研究的人中(回应率=45.4%),大多数人难以识别模型性能分析中的弱点。有必要进一步研究针对此类 ML 主题的教育干预措施。

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