人工智能用于虫病变的放射成像检测:系统性审查
Domenico Albano1,2, Vanessa Galiano3, Mariachiara Basile4
1IRCCS Istituto Ortopedico Galeazzi, Milan, Italy. albanodomenico.md@gmail.com.
BMC oral health
|February 24, 2024
概括
人工智能 (AI) 模型在检测牙病变 (CL) 方面表现有前途. 需要对更大,标准化的数据集进行进一步的研究,以优化其临床应用.
科学领域:
- 牙科 牙科是指牙科的专业.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 检测牙损伤 (CL) 对口腔健康至关重要.
- 人工智能 (AI) 提供了提高诊断准确性的潜力.
研究的目的:
- 系统地审查AI模型的诊断性能,以检测病变 (CL).
主要方法:
- 在主要数据库 (PubMed,科学网,SCOPUS,LILACS,Embase) 进行了全面的文献搜索,直到2023年1月.
- 关键词包括人工智能,机器学习,深度学习和牙.
- 使用各种AI模型 (ANN,CNN,DCNN) 对不同放射型的20项研究使用QUADAS-2指南进行了评估.
主要成果:
- 人工智能模型表现出不同的诊断性能:灵敏度 (0.44-0.86),特异性 (0.85-0.98),准确性 (0.73-0.98),以及AUC (0.84-0.98).
- 卷积神经网络 (CNN) 是最常被研究的模型.
- 大多数研究显示,根据QUADAS-2,偏差风险较低.
结论:
- 基于AI的模型显示了CL检测的良好诊断性能,可以作为有价值的临床辅助工具.
- 局限性包括数据集大小和异质性,需要以大型可比数据集进行未来研究.
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