开发基于人工智能的算法,用于通过牙科证据识别人类的过程
Cristiana Palmela Pereira1,2,3,4, Raquel Carvalho5,6,7, Diana Augusto5,6,7
1Faculdade de Medicina Dentária, Universidade de Lisboa, Rua Professora Teresa Ambrósio, 1600-277, Lisbon, Portugal. cpereira@edu.ulisboa.pt.
International journal of legal medicine
|March 6, 2025
概括
这项研究开发了一种使用卷积神经网络 (CNN) 的AI模型,用于比较来自骨科影像 (OPG) 的牙科记录,以识别未知尸体. 人工智能实现了85%的准确性,帮助法医牙科识别大规模灾难受害者.
科学领域:
- 法医牙科 法医牙科
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 法医牙科使用死前 (AM) 和死后 (PM) 牙科记录,包括骨干造牙图 (OPG),用于医疗法律识别.
- 目前的识别方法复杂且耗时,需要通过先进的成像分析进行优化.
- 卷积神经网络 (CNN) 提供了一个有前途的AI解决方案,用于在法医环境中高效和详细的牙图像分析.
研究的目的:
- 开发和评估CNN算法,用于比较OPG中的AM和PM牙科证据.
- 通过使用人工智能驱动的OPG分析来增强未知尸体的医疗法律识别.
- 评估算法在年龄分类和正确识别方面的有效性.
主要方法:
- 从1050名年龄在16-30岁的患者中使用了1235个OPG.
- 基于VGG16预训练模型开发了两个CNN算法:一个用于年龄分类,一个用于正确识别.
- 使用预测指标和热图评估算法性能.
主要成果:
- 两种CNN模型的整体准确率达到了85%.
- 年龄分类模型在16-23岁的个体中显示出更高的准确性.
- 积极识别模型在区分OPG与不同个体方面表现出卓越的表现.
结论:
- 开发的AI模型有效地帮助医疗法律识别未知尸体.
- 人工智能模型在大规模灾难受害者识别场景中表现出特别有用的效用.
- 该模型专门用于16至30岁的个人OPG的验证.
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