在眼部瘤诊断中对人工智能模型进行系统审查
Kyran Sachdeva1, Fahad R Butt2, Andrew Mihalache3
1Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
|January 18, 2026
概括
人工智能 (AI) 显示出对诊断眼睛瘤的前景,在各种眼部部分实现高精度. 然而,需要进一步的研究来比较AI.
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:
- 眼部瘤显著影响患者的生活质量和生存率.
- 人工智能 (AI) 已经证明了诊断能力的增加.
- 本综述评估了AI对外部,前置和后置眼瘤的诊断性能.
研究的目的:
- 系统地审查和评估AI模型在识别眼睛瘤方面的诊断性能.
- 评估AI在不同眼睛瘤分类中的准确性,敏感性和特异性.
主要方法:
- 在Embase,MEDLINE和Cochrane图书馆 (2000年1月至2025年1月) 进行了系统的文献搜索.
- 研究集中在眼睛瘤诊断中的AI,提取定量结果,如准确性,灵敏性和特异性.
- 使用 QUADAS-2 工具来评估包含的研究的偏差风险和适用性.
主要成果:
- 包括23项研究,分析了对外部 (12),前部 (2) 和后部 (8) 眼瘤的AI性能.
- 权重平均AI准确度在外部瘤中达到91.4%,后部瘤中达到89.8%,前部瘤中达到98.5%.
- 在大多数研究中,人工智能诊断的准确性与医生的准确性相当,尽管有些研究显示眼科医生表现优越.
结论:
- 人工智能工具为有效和准确的眼睛瘤诊断提供了潜在的途径.
- 进一步的比较研究对于验证AI与眼科医生的诊断性能至关重要.
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