非眼科医生医生对人工智能增强的 fundus 疾病进行查:一项结合前后研究
EunAh Kim1, Su Jeong Song2,3
1Department of Ophthalmology, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon 51353, Republic of Korea.
Bioengineering (Basel, Switzerland)
|December 30, 2025
概括
一个人工智能工具显著提高了全科医生对视网膜疾病的诊断准确度,提高了初级保健中的查和转诊决策. 这种人工智能 (AI) 支持有助于非眼科医生检测诸如绿眼病等疾病.
科学领域:
- 眼科医生 眼科 眼科
- 医疗成像医学成像
- 医疗保健中的人工智能
背景情况:
- 视网膜疾病查正在扩大初级保健,通常由非专家进行,精度可变.
- 对眼科服务的有限访问需要在初级保健机构提高诊断能力.
研究的目的:
- 评估基于人工智能的决策支持工具,以提高非眼科医生在视网膜疾病查中的诊断准确性.
- 评估人工智能协助对全科医生转诊决定的影响.
主要方法:
- 采用了一种对比的前后研究设计.
- 四位非眼科医生审查了500张彩色 fundus 照片,首先没有人工智能协助,然后在洗期后得到人工智能支持.
- 在无辅助和人工智能辅助审查中比较了诊断准确度和转诊决策.
主要成果:
- 人工智能辅助显著提高了诊断准确度,从82.8%提高到91.1% (p < 0.0001).
- 最显著的改善是在识别可疑的青光眼病例和患有多种病理的患者中进行的.
- 观察到有利的安全性,临床医生保留了最终的诊断权.
结论:
- 人工智能辅助的诊断工具可以有意义地增强非眼科医生在初级保健中的查和转诊能力.
- 这些发现支持整合人工智能决策支持,以改善视网膜疾病的现实世界初级保健.
- 建议进行进一步的验证和实施研究,以扩大这种技术的应用.
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