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基于人工智能的两种方法来评估土耳其儿童的骨龄的比较:BoneXpert和VUNO Med-Bone Age
Evrim Özmen1, Hande Özen Atalay1, Evren Uzer1
1Koç University Hospital, Department of Radiology, İstanbul, Türkiye.
Diagnostic and interventional radiology (Ankara, Turkey)
|September 2, 2024
概括
人工智能 (AI) 骨年龄评估工具BoneXpert和VUNO Med-Bone Age (VUNO) 在土耳其儿童中显示出高有效性. 这两种AI程序都与手动评估有很好的一致性,证明了对儿科骨年龄评估的可靠性.
科学领域:
- 儿科放射学 儿科放射学
- 人工智能在医学中的应用
- 骨发育评估 骨发育评估
背景情况:
- 准确的骨龄评估对于评估儿科生长和发育至关重要.
- 像Greulich-Pyle方法这样的传统方法需要专家的解释,并且可能耗费大量时间.
- 新兴的人工智能 (AI) 工具为更快,更一致的骨年龄确定提供了潜力.
研究的目的:
- 为了评估两个基于AI的骨年龄评估程序BoneXpert和VUNO Med-Bone Age (VUNO) 的诊断有效性.
- 在一组土耳其儿童中,将这些AI工具的性能与已建立的手动Greulich-Pyle方法进行比较.
主要方法:
- 对292例儿科病例 (1-15岁) 进行了回顾性分析.
- 两个独立的放射科医生进行了手动骨年龄评估,不知道AI的结果.
- 类内相关系数 (ICC) 用于测量手动和基于AI的评估之间的一致性.
主要成果:
- 无论是BoneXpert还是VUNO,都显示出与手动评估的高度一致性,ICC值显示出几乎完美的相关性.
- 在不同的年龄和性别小组中,BoneXpert和VUNO之间没有发现统计学上显著的准确性差异.
- 人工智能工具在所有分析的儿科病例中表现一致.
结论:
- BoneXpert和VUNO Med-Bone Age是土耳其儿童骨年龄评估的有效和可靠的工具.
- 基于人工智能的方法与手动评估具有很高的一致性,适合临床应用.
- 这项研究是第一个在土耳其儿科人口中验证这些AI工具的研究.
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