国际眼科纵览 ›› 2022, Vol. 46 ›› Issue (2): 189-192.doi: 10.3760/cma.j.issn.1673-5803.2022.02.017

• 综述 • 上一篇    

人工智能在屈光手术中的研究与应用进展

刘盼  邵正波   

  1. 哈尔滨医科大学附属第二医院眼科 未来医学实验室 150086
  • 收稿日期:2021-07-24 出版日期:2022-04-22 发布日期:2022-04-24
  • 通讯作者: 邵正波,Email:shaozhengbohmu@126.com
  • 基金资助:
    国家自然科学基金(81970799);黑龙江省博士后科研启动基金(LBH-Q18082);哈尔滨医科大学实践创新项目(YJSCX2020102HYD)

Advances for application of artificial intelligence in refractive surgery

Liu Pan, Shao Zhengbo   

  1. Department of Ophthalmology, Future Medical Laboratory, the Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China
  • Received:2021-07-24 Online:2022-04-22 Published:2022-04-24
  • Contact: Shao Zhengbo, Email: shaozhengbohmu@126.com
  • Supported by:
    National Natural Science Foundation of China (81970799); Heilongjiang Postdoctoral Scientific Research Developmental Fund (LBH-Q18082); Harbin Medical University Graduate Innovation and Practice Research Project (YJSCX2020102HYD)

摘要: 人工智能(artificial intelligence,AI)在屈光手术的术前圆锥角膜筛查、屈光手术方案选择、手术参数设计、术后疗效预测以及有晶状体眼后房型人工晶状体植入术(implantable collamer lens,ICL)术后拱高预测等方面的应用研究取得了一定进展。AI在早期圆锥角膜识别方面普遍具有较高的准确度;AI辅助医生进行屈光手术方案选择和手术参数设计,有利于提升患者术后视觉质量;AI进行角膜屈光手术术后疗效预测,显示预测结果与实际结果具有良好的相关性。此外,AI对ICL术后拱高预测也显示出良好性能。(国际眼科纵览,2022, 46:189-192)


关键词: 人工智能, 机器学习, 屈光手术

Abstract: In the field of refractive surgery, artificial intelligence (AI) has been widely applied in screening keratoconus, selecting scheme of refractive surgery, designing nomogram, predicting the postoperative effect of cornea refractive surgery and the vault of implantable collamer lens (ICL). AI could improve the accuracy of subclinical keratoconus screening. AI assisted doctors in selecting scheme of refractive surgery and designing nomogram to improve the postoperative visual quality of patients. AI predicted the postoperative efficacy of cornea refractive surgery and showed a good correlation between the predicted efficacy and actual efficacy. In addition, AI exhibited good performance in predicting the vault of ICL.(Int Rev Ophthalmol, 2022, 46:  189-192)


Key words: artificial intelligence, machine learning, refractive surgery