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Author Spotlight: Advancements in Refractive Surgical Correction for Presbyopia and Exploring Postoperative Visual Acuity
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[机器学习应用在折射手术中的进步]

J H Wang1, Y L Peng1

  • 1Aier College of Ophthalmology, Central South University, Changsha 410000, China.

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
|April 7, 2025
PubMed
概括

机器学习通过改善患者查,手术规划和预测结果来增强折射手术. 解决算法透明度和数据整合挑战是其更广泛采用的关键.

科学领域:

  • 眼科医生 眼科 眼科
  • 人工智能的人工智能
  • 医疗信息学 医疗信息学

背景情况:

  • 折射误差严重影响视力,并造成经济负担.
  • 目前的折射手术在查,规划和预防并发症方面面临着挑战.

研究的目的:

  • 审查机器学习在折射手术中的应用和局限性.
  • 确定该领域未来的研发领域.

主要方法:

  • 在折射手术中对机器学习应用的综合文献分析.
  • 对现有关于机器学习在不同手术阶段的作用的研究进行系统审查.

主要成果:

  • 机器学习提高了皮的查准确度和候选人选择.
  • 它优化了角膜手术和透镜植入手术计划,提高了可预测性.
  • 机器学习助力术后评估,回归风险识别和眼内透镜功率计算.

结论:

  • 机器学习在折射手术阶段提供了显著的好处.
  • 局限性包括算法不透明性,数据质量问题和数据整合挑战.
  • 需要进一步的研究,以促进机器学习在折射手术中的更深入,更合理的应用.

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