用SD-OCT图像检测青光瘤的人工智能:系统审查和元分析
Nan-Nan Shi1,2, Jing Li1,2, Guang-Hui Liu1,2
1Department of Ophthalmology, Affiliated People's Hospital (Fujian Provincial People's Hospital), Fujian University of Traditional Chinese Medicine, Fuzhou 350004, Fujian Province, China.
International journal of ophthalmology
|May 9, 2024
概括
人工智能 (AI) 在使用光谱域光学连贯性断层扫描 (SD-OCT) 图像检测青光眼时表现出高精度. 将人工智能与专家临床医生结合起来,可以提高青光眼的诊断和患者的治疗结果.
科学领域:
- 眼科医生 眼科 眼科
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 玻璃眼是全球不可逆转的失明的主要原因.
- 早期和准确的诊断对于有效的管理和视力保护至关重要.
- 谱域光学连贯断层扫描 (SD-OCT) 提供了视神经头部和视网膜神经纤维层的详细横截图.
研究的目的:
- 使用SD-OCT图像系统评估人工智能 (AI) 算法的诊断性能,以检测青光眼.
- 量化基于人工智能的玻璃眼瘤检测模型的聚合灵敏度,特异性和其他诊断指标.
- 评估人工智能的潜力,作为改善青光眼诊断的辅助工具.
主要方法:
- 在主要的电子数据库 (PubMed,Embase,Scopus等) 中进行了全面的文献搜索. 对于在2023年5月31日之前发表的研究.
- 20项研究包括51个AI模型,用于使用SD-OCT检测青光瘤,这些研究被选中进行系统审查和元分析.
- 进行了统计分析,包括元分析,元回归,子组分析和偏差评估 (使用QUADAS-2工具).
主要成果:
- 分析显示,在青光眼检测中AI的综合灵敏度为0.91和特异性为0.90.
- 聚合的正概率 (PLR) 是8.79和负概率 (NLR) 是0.11.
- 人工智能模型的曲线下的面积 (AUC) 高达0.95,表明诊断准确度很好,没有观察到显著的值效应.
结论:
- 在使用SD-OCT成像时,AI在检测青光眼方面表现出很高的准确性.
- 基于人工智能的算法,特别是当与"医生+人工智能"方法结合使用时,显示出改善青光眼的诊断准确性的重大承诺.
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