人工智能应用在下三冲击病例中:对文献的系统审查
Hassan Ahmed Assiri1, Mohammad Shahul Hameed1, Abdullah Alqarni1
1Department of Diagnostic Science and Oral Biology, College of Dentistry, King Khalid University, P.O. Box 960, Abha City 61421, Saudi Arabia.
Journal of clinical medicine
|August 10, 2024
概括
人工智能 (AI) 在分析受冲击的下第三牙方面表现有前途,准确评估它们与下膜神经通道的关系. 需要进一步的研究来完善AI.
科学领域:
- 牙科 牙科是指牙科的专业.
- 口腔和牙面部外科手术
- 医疗保健中的人工智能
背景情况:
- 受影响的下第三牙会带来诊断和治疗规划方面的挑战.
- 准确评估受影响的牙与相邻的解剖结构的关系,特别是下膜神经通道,对于手术安全至关重要.
研究的目的:
- 系统地审查和总结现有关于人工智能 (AI) 在被冲击下第三的诊断和管理中的应用证据.
- 评估AI在这种特定的牙科环境中的当前能力和局限性.
主要方法:
- 在PubMed,Scopus和谷歌学者中进行了系统的文献搜索.
- 纳入标准侧重于人工智能应用,用于诊断,治疗和规划与受影响的下第三关节相关.
- 选择了21篇文章,并使用苏格兰大学间指南网络 (SIGN) 尺度对其质量进行了评估.
主要成果:
- 人工智能模型在确定受冲击的下第三和下通道之间的形态学,解剖学和空间关系方面表现出熟练.
- 包含的研究的平均质量是SIGN 2+,相当于证据水平B.
- 大多数研究都专注于人工智能能够映射受影响的关骨相对于下膜神经的位置.
结论:
- 人工智能在对受影响的下第三的解剖学评估中显示出与人类观察者相当或更高的性能.
- 目前的人工智能模型处于早期发展阶段,可以预测牙喷发和长期结果.
- 进一步的研究是必不可少的,以开发全面的AI模型来预测第三口喷发和优化治疗结果.
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