PRIME 2.0:对心血管成像相关机器学习评估清单的建议要求的更新
Nobuyuki Kagiyama1, Márton Tokodi2, Quincy A Hathaway3
1Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan; AI Incubation Farm, Juntendo University Faculty of Medicine, Tokyo, Japan.
PRIME 2.0 清单提供了有关心血管成像人工智能 (AI) 开发和报告的最新指导. 这一框架涉及深度学习和大型语言模型等新型人工智能技术,以提高研究透明度.
科学领域:
- 心血管成像
- 人工智能
- 医疗信息学
背景情况:
- 人工智能 (AI) 的快速发展,包括深度学习和大型语言模型,需要更新心血管成像中的AI应用报告标准.
- 现有的AI报告准则缺乏复杂心血管成像研究所需的具体性.
- 最初的PRIME检查清单提供了一个基础框架,但需要加强以解决当前的人工智能技术和特定领域的挑战.
研究的目的:
- 介绍更新的PRIME 2.0检查清单,这是一个特定领域的框架,用于标准化心血管成像中的AI的开发,评估和报告.
- 将近期的人工智能进步,如深度学习和生成的人工智能纳入报告准则.
- 根据心血管成像的独特复杂性提供实用建议,包括运动,工件和可变性.
主要方法:
- 在开发PRIME2.0清单时,使用了修改后的Delphi程序.
- 一个由临床和技术专家组成的国际小组为清单的完善做出了贡献.
- 该框架建立在原有的七个领域结构上,整合了心血管成像的具体考虑.
主要成果:
- PRIME 2.0 清单为心血管成像中的人工智能研究提供了详细的实用建议.
- 它解决了人工智能开发,评估和报告的关键方面,超越了一般指导方针.
- 检查清单包括特定的挑战,如心脏运动,成像工件和观察者之间的变化.
结论:
- 在心血管成像中提高AI研究的透明度和严格性.
- 它是研究人员,临床医生,同行评审和编辑的重要资源.
- 采用PRIME 2.0可以提高现场人工智能应用的质量和可靠性.
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