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基于人工智能的糖尿病视网膜病变查在澳大利亚的初级保健和内分泌学环境中的有效性:实用试验
Sanil Joseph1,2,3, Yueye Wang4, Jocelyn J Drinkwater5,6
1Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia sanil@aravind.org lisa.zhu@unimelb.edu.au mingguang.he@polyu.edu.hk.
The British journal of ophthalmology
|August 22, 2025
概括
基于人工智能的糖尿病视网膜病变查模型在澳大利亚诊所表现出高准确性. 这种自动化系统有望在非眼科环境中及早发现和预防视力损失.
科学领域:
- 眼科 眼科
- 人工智能
- 主要护理医学
背景情况:
- 糖尿病视网膜病变 (DR) 是可预防的失明的主要原因.
- 早期发现和及时治疗对于治理DR至关重要.
- 将人工智能整合到初级保健中可以提高查的可用性.
研究的目的:
- 评估人工智能驱动的DR查工具的诊断准确性.
- 评估AI模型在澳大利亚初级保健和内分泌学环境中的可行性和用户体验.
- 确定AI对机会性DR查的潜力.
主要方法:
- 这是一项实用性试验,涉及澳大利亚诊所18岁以上的863名糖尿病患者.
- 使用人工智能集成的非水底摄像头进行查.
- 人工智能分级精度与人类分级的黄金标准进行比较.
主要成果:
- 人工智能系统在可引用的DR检测中获得了93.3%的准确性 (灵敏度为83.7%,特异性为96.1%).
- 人工智能模型的不可分类图像比例 (13.4%) 与人类分类 (15.6%) 相比较低.
- 86% 的患者和 85% 的护理人员报告高满意度.
结论:
- 在澳大利亚的初级保健和内分泌学环境中,人工智能辅助的DR查模型是准确且受欢迎的.
- 这种自动化系统为机会性DR查提供了一个有前途的方法.
- 广泛实施可以显著提高早期DR检测和预防视力丧失.
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