机器学习技术用于牙周炎和牙腐烂的检测:一个叙事审查
R C Radha1, B S Raghavendra1, B V Subhash2
1Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Surathkal, India.
International journal of medical informatics
|August 18, 2023
概括
机器学习 (ML) 在诊断牙周炎和牙损伤方面表现有前途. 使用智能手机图像来训练ML模型,为早期检测的传统方法提供了一个具有成本效益的,准确的替代方案.
科学领域:
- 牙科诊断 牙科诊断 牙科诊断
- 机器学习应用程序 机器学习应用程序
- 医疗保健中的人工智能
背景情况:
- 牙周炎和牙损是普遍存在的口腔健康问题,需要及早诊断以防止牙脱落.
- 目前的诊断方法依赖于经验丰富的牙医进行视觉检查,探测和放射.
- 机器学习 (ML) 算法用于自动牙科诊断的临床适用性仍在调查中.
研究的目的:
- 审查和分析用于自动检测牙周炎和牙损伤的机器学习应用程序.
- 确定目前用于牙科诊断的ML方法的研究挑战和局限性.
- 探索开发可靠的ML系统的途径,用于临床使用和临床检测.
主要方法:
- 从2015年到2022年在PubMed,IEEE Xplore和ScienceDirect中进行了广泛的文献搜索.
- 包括55项专注于ML的研究,用于检测牙周炎,牙损伤和相关问题.
- 基于选定的研究,对ML技术及其诊断准确性的分析.
主要成果:
- 大多数ML研究都使用放射图像进行牙科诊断.
- 一些研究表明,使用智能手机拍摄的图像具有很高的诊断准确性.
- ML的应用包括牙周炎,牙腐烂,牙顶部病变,牙周骨损失和垂直根骨折.
结论:
- 基于智能手机的ML模型可以实现牙科问题的良好诊断准确性.
- 使用智能手机图像可以降低临床诊断成本,提高用户交互.
- 需要进一步的研究来克服局限性,并建立强大的ML系统,以便在临床上广泛采用.
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