使用人工智能的研究应该如何报告? 从心脏MRI系统审查中得出的教训
Ahmed Maiter1,2, Mahan Salehi1, Andrew J Swift1,2
1Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Frontiers in radiology
|July 26, 2023
概括
在心脏MRI细分研究中,人工智能 (AI) 的报告质量往往很差. 改进报告标准对于推进心血管医学中的AI和确保可靠的临床翻译至关重要.
科学领域:
- 心血管成像 - 心血管成像
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 人工智能 (AI) 工具越来越多地用于心脏MRI (CMR) 分段.
- 高质量的报告对于这些AI工具的进步和临床采用至关重要.
- 之前的审查强调了人工智能医学成像研究中的可变报告标准.
研究的目的:
- 系统地评估使用人工智能进行心脏MRI细分的研究报告质量.
- 确定研究报告中的常见缺陷.
- 为改善未来在这个领域的研究报告提供建议.
主要方法:
- 进行了一项系统性审查,评估了209项研究.
- 研究被评估是否符合医学成像AI检查清单 (CLAIM).
- 特别评估了模型描述,研究设计,数据集和性能的报告.
主要成果:
- 对于模型描述 (100%) 符合CLAIM的程度很高,但对于研究设计 (71%),数据集 (63%) 和性能 (60%) 则较低.
- 在出版物中发现了大量和频繁的信息缺口.
- 总体而言,报告质量不稳定,有时甚至很差.
结论:
- 对于心脏MRI细分研究,AI中的报告质量需要大幅度改进.
- 遵守CLAIM等报告准则对于透明度和可重复性至关重要.
- 增强的报告将促进AI工具在心脏病学中的批判性评估和临床翻译.
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