医学人工智能的指导方针和标准框架:系统文献审查议定书
Kirubel Biruk Shiferaw1, Moritz Roloff1, Dagmar Waltemath1
1Department of Medical Informatics, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
JMIR research protocols
|October 25, 2023
概括
本次审查评估了医学人工智能 (AI) 的指导方针,以确保可靠的AI模型开发和实施. 对医疗保健提供者来说,评估指南质量至关重要,以自信地采用人工智能工具.
科学领域:
- 生物医学科学 生物医学科学
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 人工智能 (AI) 在生物医学科学中的应用越来越多,由于模型的"黑子"性质和缺乏标准化指南,这给医疗保健提供者带来了挑战.
- 针对特定疾病的多个AI模型造成不确定性,阻碍了对临床环境的信任和实际实施.
- 对人工智能开发和报告缺乏一致的指导方针使得这些技术在医学中的采用变得复杂.
研究的目的:
- 审查和综合有关AI在医学应用现有指导方针和框架质量的证据.
- 评估当前指南的可靠性和有效性,以促进AI在医疗保健中的开发,报告和实施.
- 确定当前指导方针中的差距,并为医疗应用中人工智能的未来研究方向提供信息.
主要方法:
- 使用医学学科标题对医学,指南和机器学习 (ML) 进行系统的文献搜索.
- 包括所有可用的指南,框架,最佳实践,检查清单和来自PubMed,Web of Science和EQUATOR等存储库的建议.
- 使用"指导方针,研究和评估评估" (AGREE II) 工具对确定指导方针进行质量评估,然后进行描述性摘要和叙事综合.
主要成果:
- 审查将根据PRISMA (系统性审查和元分析的首选报告项目) 准则报告调查结果.
- 数据分析正在进行中,预计将于2023年11月完成.
- 结果将提供指南质量和方面的描述性摘要和叙事综合.
结论:
- 高质量的指导方针对于可靠的评估和医学应用中的ML模型的一致解释至关重要.
- 评估可用的指南,建议和框架的质量对于了解当前的局限性至关重要.
- 这次审查将全面了解人工智能指导方针中的差距,指导医疗人工智能的未来研究和开发.
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