摘要
圆锥角膜的诊断与人工智能息息相关,而机器学习是人工智能的核心,各种结合了角膜形态数据的机器学习模型是圆锥角膜诊断中的有效补充,并提供了一定的决策支持,这类人工智能系统可以提高读图效率、减少人为误判几率并有效降低人力成本。本文通过归纳既往辅助诊断圆锥角膜的机器学习模型,帮助研究者们了解圆锥角膜智能诊断领域的相关知识,这对于进一步开展这一领域的机器学习研究有重要意义。
The diagnosis of keratoconus is closely related to artificial intelligence.Machine learning is the core of artificial intelligence,machine learning models combined with corneal information are effective supplements in keratoconus diagnosis and provide decision support.These artificial intelligence systems can bring efficiency,reduce artificial misjudgment and effectively reduce manpower costs.In this paper,by summarizing the previous machine learning models that assisted the diagnosis of keratoconus,we may help researchers understand the relevant knowledge in the field of intelligent diagnosis of keratoconus,which is of great significance for further machine learning research.
作者
谢怡
刘泉
Xie Yi;Liu Quan(Department of Ophthalmology,Shenzhen People′s Hospital,Second Clinical Medical College of Jinan University,First Affiliated Hospital of Southern University of Science and Technology,Shenzhen 518020,China;Zhongshan Ophthalmic Centre,Sun Yat-sen University,State Key Laboratory of Ophthalmology,Guangzhou 510060,China)
出处
《中华眼科杂志》
CAS
CSCD
北大核心
2022年第10期854-858,共5页
Chinese Journal of Ophthalmology
基金
国家自然科学基金(31671000)
广州市科技计划项目(201804020007)。
关键词
圆锥角膜
机器学习
人工智能
角膜地形图
Keratoconus
Machine learning
Artificial intelligence
Corneal topography
