在全景射线图上人工智能辅助的动脉结的诊断:一个元分析
Fangfei Ye1, Qun Zhou2, Siying Zhang3
1Department of Stomatology, Shaoxing Hospital of Traditional Chinese Medicine, Shaoxing, Zhejiang, China.
International dental journal
|February 8, 2026
概括
人工智能 (AI) 在全景放射图 (PRs) 上检测动脉化 (CACs) 时显示出高精度,帮助牙医识别中风风险因素. 需要进一步的大规模研究来证实这些对CAC检测的有希望的发现.
科学领域:
- 口腔放射学是一门口腔放射学专业.
- 心血管健康的心血管健康
- 医学中的人工智能
背景情况:
- 动脉结 (CACs) 是一个重要的中风风险因素.
- 在全景射线图 (PRs) 上可以检测到CAC.
- 牙医由于有限的培训和专业知识,往往低估了CAC的诊断.
研究的目的:
- 评估人工智能 (AI) 的诊断准确性,以检测PRs上的CAC.
- 评估AI的潜力,作为一种工具,帮助牙医识别CAC.
主要方法:
- 在主要数据库 (PubMed,Embase,Web of Science,Scopus,Cochrane Library) 中进行了全面的文献搜索.
- 通过QUADAS-2工具评估研究质量.
- 用Stata 14.0进行了元分析,分析了7项符合条件的研究的数据,从每方和每人角度来看.
主要成果:
- 每侧分析显示了高的诊断准确性:灵敏度为0.88,特异性为0.94,AUC为0.96.
- 每人分析显示灵敏度为0.90,特异性为0.81,AUC为0.86.
- 人工智能表现出强大的绩效指标,包括积极和消极的概率比和诊断几率比.
结论:
- 人工智能显示出显著的潜力,作为一种有价值的工具,帮助牙医检测PRs上的CAC.
- 人工智能可以帮助克服与牙医专业知识相关的诊断挑战.
- 需要进一步的大规模,基于证据的研究来验证AI在临床实践中的有效性.
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