增强决策:人工智能增强了对青光眼诊断和治疗的准确性
Marco Zeppieri1,2, Caterina Gagliano3,4, Daniele Tognetto2
1Department of Ophthalmology, University Hospital of Udine, 33100 Udine, Italy.
Journal of clinical medicine
|September 27, 2025
概括
人工智能 (AI) 和增强型智能 (AuI) 在青光眼治疗中显示出巨大的前景,改善了早期检测和治疗预测. 虽然存在诸如偏见之类的挑战,但AI/AuI可以增强临床医生的专业知识,以获得更好的患者结果.
科学领域:
- 眼科医生 眼科 眼科
- 医疗人工智能 医疗人工智能
- 医疗信息学 医疗信息学
背景情况:
- 玻璃眼是全球不可逆转失明的主要原因.
- 人工或增强型智能 (AI/AuI) 越来越多地应用于青光眼治疗.
- 该审查涵盖了从2019年1月到2025年7月的研究.
研究的目的:
- 审查AI/AuI在青光眼治疗中的应用.
- 评估AI/AuI工具在临床实践中的有效性和挑战.
- 了解AI/AuI对眼病管理和患者获取的潜在影响.
主要方法:
- 对超过150项同行评审的AI/AuI在青光眼中的研究进行系统审查.
- 深度学习,序列意识,多式联络和大型语言模型的分析.
- 评估AI/AuI性能指标,包括AUC,灵敏度和特异性.
主要成果:
- 深度学习模型在分析基金照片和OCT卷时实现了AUC~0.95.
- 序列感知模型预测视野恶化早到了1.7年.
- 多模式网络预测了手术需要 (AUROC 0.92);智能手机分类显示高灵敏度 (94%) 和特异性 (86-94%).
- 大型语言模型在案例问题答案中表现出专家级准确性.
结论:
- AI/AuI系统在诊断青光眼和预测疾病进展方面表现出高准确度.
- 人工智能/人工智能工具在资源较少的环境中是可行的,可以帮助早期干预.
- 关键的挑战包括算法偏见,工作流集成和监管合规 (例如,欧盟人工智能法,FDA GMLP).
- 严格的验证和偏见审计对于AI/AuI来说至关重要,以增加临床医生的专业知识并改善全球眼治疗的准入.
关键词:
人工智能的人工智能是人工智能.增强智能是一种增强智能.临床决策支持 临床决策支持深度学习是一种深度学习.可以解释的人工智能AI联合学习的联合学习玻璃眼 glaucoma 玻璃眼 玻璃眼 玻璃眼 玻璃眼光学连贯性断层扫描技术远程眼科医生 远程眼科医生视野 视野 视野 视野 视野更多相关视频
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