基于OCT的视网膜异常查系统在真实临床环境中的人工智能云平台
Xinjian Chen1,2, Jingtao Wang3, Tianwei Qian4,5,6,7,8
1School of Electronics and Information Engineering, Soochow University, Suzhou, China. xjchen@suda.edu.cn.
NPJ digital medicine
|August 29, 2025
概括
对视网膜异常查的AI平台显著改善了中国的远程诊断. 这种AI-PORAS系统与眼科医生的表现相匹配,
科学领域:
- 眼科 眼科
- 人工智能
- 医学成像
背景情况:
- 全球有数百万人患有视网膜异常, 面临不可逆转的视力损失.
- 中国面临眼科医生严重短缺, 尤其是在农村地区.
- 现有的诊断方法因患者与专家的高比例而受到压力.
研究的目的:
- 开发和验证基于OCT的视网膜异常查人工智能云平台 (AI-PORAS).
- 提高15种常见的视网膜异常的远程诊断效率.
- 为改善医疗保健决策和治疗规划提供数据.
主要方法:
- 使用人工智能开发AI-PORAS平台.
- 对光学一致性断层扫描 (OCT) B扫描图像的大数据集进行培训和验证.
- 部署到中国29个省份的207个医疗机构,
主要成果:
- 在检测15种视网膜异常时,AI- PORAS显示出高准确度 (93. 16%) 和AUC (93. 64%).
- 性能指标 (FPR 6. 82%,FNR 7. 87%) 与眼科医生的表现相当.
- 验证包括165,384只眼睛和3,551,959个OCTB扫描片.
结论:
- 使用OCT图像有效选视网膜异常,解决专家短缺问题.
- 该平台的性能与经验丰富的眼科医生相美, 提高了远程诊断能力.
- 对116,717名远程诊断患者的统计分析为公共卫生策略提供了宝贵的见解.
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