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贴近实践:技术在评估新时代中的作用。

Proximity to Practice: The Role of Technology in the Next Era of Assessment.

作者信息

Krumm Andrew E, Lai Hollis, Marcotte Kayla, Ark Tavinder K, Yaneva Victoria, Chahine Saad

机构信息

Learning Health Sciences, Surgery, and Information, Medical School and School of Information, University of Michigan, Ann Arbor, Michigan, United States.

Faculty of Medicine and Dentistry, University of Alberta, Canada.

出版信息

Perspect Med Educ. 2024 Dec 26;13(1):646-653. doi: 10.5334/pme.1272. eCollection 2024.

DOI:10.5334/pme.1272
PMID:39735827
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11673589/
Abstract

The integration of technology into health professions assessment has created multiple possibilities. In this paper, we focus on the challenges and opportunities of integrating technologies that are used during clinical activities or that are completed by raters after a clinical encounter. In focusing on technologies that are more proximal to practice, we identify tradeoffs with different data collection approaches. To maximize the benefits of integrating technology in workplace-based assessment, we describe the importance of using preexisting frameworks from the fields of assessment design, implementation research, and clinical artificial intelligence governance.

摘要

将技术整合到健康职业评估中创造了多种可能性。在本文中,我们关注整合临床活动中使用的技术或临床接触后评分者完成的技术所带来的挑战和机遇。在关注更贴近实践的技术时,我们确定了不同数据收集方法之间的权衡。为了最大限度地提高将技术整合到基于工作场所的评估中的益处,我们描述了使用评估设计、实施研究和临床人工智能治理领域的现有框架的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4755/11673589/293e9d4c376d/pme-13-1-1272-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4755/11673589/293e9d4c376d/pme-13-1-1272-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4755/11673589/293e9d4c376d/pme-13-1-1272-g1.jpg

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Considering the Secondary Use of Clinical and Educational Data to Facilitate the Development of Artificial Intelligence Models.考虑将临床和教育数据的二次使用用于促进人工智能模型的开发。
Acad Med. 2024 Apr 1;99(4S Suppl 1):S77-S83. doi: 10.1097/ACM.0000000000005605. Epub 2023 Dec 18.
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Precision Medical Education.精准医学教育。
Acad Med. 2023 Jul 1;98(7):775-781. doi: 10.1097/ACM.0000000000005227. Epub 2023 Apr 3.
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Ethical use of Artificial Intelligence in Health Professions Education: AMEE Guide No. 158.卫生专业教育中人工智能的伦理应用:AMEE指南第158号
Med Teach. 2023 Jun;45(6):574-584. doi: 10.1080/0142159X.2023.2186203. Epub 2023 Mar 13.
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Artificial Intelligence Screening of Medical School Applications: Development and Validation of a Machine-Learning Algorithm.人工智能筛选医学院申请:机器学习算法的开发与验证。
Acad Med. 2023 Sep 1;98(9):1036-1043. doi: 10.1097/ACM.0000000000005202. Epub 2023 Mar 6.
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The fundamentals of Artificial Intelligence in medical education research: AMEE Guide No. 156.医学教育研究中的人工智能基础:AMEE指南第156号
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