医疗保健中的AI质量标准:快速总体审查
Craig E Kuziemsky1, Dillon Chrimes2, Simon Minshall2
1MacEwan University, Edmonton, AB, Canada.
Journal of medical Internet research
|May 22, 2024
概括
尽管医疗研究中有许多人工智能 (AI) 质量标准,但它们很少在实践中使用. 研究人员必须采用这些不断变化的AI标准,以提高研究质量并解决道德问题.
科学领域:
- 医疗保健信息学 医疗保健信息学
- 人工智能在医学中的应用
- 系统审查方法论 系统审查方法论
背景情况:
- 人工智能 (AI) 在医疗保健研究中的普及需要强有力的评估标准.
- 现有的AI质量标准旨在评估医疗保健AI研究的严格性.
研究的目的:
- 在医疗保健系统审查中对人工智能质量标准进行快速综合审查.
- 检查AI质量标准在出版文献中的应用和有效性.
主要方法:
- 采用了Joanna Briggs研究所修改后的综合审查方法.
- 在MEDLINE和Google Scholar的专注搜索中,发现了提到人工智能和健康的英语系统评论.
- 包括的评论分析了AI质量标准的使用情况,并确定了问题.
主要成果:
- 综合了33项系统性审查 (2020-2022年),涵盖了医疗保健中的各种AI应用.
- 人工智能质量标准仅在39%的审查和14%的初级研究中被应用.
- 透明度,道德和隐私等关键质量方面很少被解决,突出了标准化的需要.
结论:
- 尽管医疗保健AI质量标准的可用性日益增加,但仍未得到充分利用.
- 采用不断变化的AI质量标准对于提高医疗保健AI研究的可靠性和可信度至关重要.
- 对未来的人工智能研究来说,解决道德,社会和监管方面的影响至关重要.
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