用垂直植入式拼接镜头植入眼睛中的圆顶预测
Ryuichi Shimada1, Satoshi Katagiri, Hiroshi Horiguchi
1From the Eye Clinic Tokyo, Tokyo, Japan (Shimada, Kitazawa); Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan (Shimada, Katagiri, Horiguchi, Nakano).
Journal of cataract and refractive surgery
|October 1, 2024
概括
新的公式和机器学习模型改善了在垂直植入式眼镜 (ICL) 手术中术后顶的预测. 这些进步为ICL植入结果提供了更高的精度.
科学领域:
- 眼科医生 眼科 眼科
- 生物医学工程 生物医学工程
- 数据科学数据科学数据科学
背景情况:
- 准确的术后预测对于成功的垂直植入式合镜片 (ICL) 植入至关重要.
- 现有的方法可能缺乏为最佳患者结果所需的精度.
研究的目的:
- 开发用于垂直ICL植入的术后的预测公式.
- 通过使用先进的机器学习模型来提高预测准确性.
主要方法:
- 从408名接受垂直ICL植入的患者的720只眼睛的回顾性分析.
- 使用多重线性回归的三个预测公式 (V1-V3) 的开发.
- 评估四种机器学习模型,包括极端梯度提升和随机森林回归器.
主要成果:
- V1-V3公式显示了可比性能,平均绝对误差在122.90±103.00μm到127.97±107.92μm之间.
- 极端梯度提升和随机森林回归模型显示出优异的预测准确性.
- 机器学习模型实现的平均绝对误差分别为118.31 ± 100.55 μm和118.63 ± 99.34 μm.
结论:
- 该研究引入了用于垂直ICL植入室预测的新型V1-V3公式.
- 更简单的公式 (V1,V2) 在较少的参数下提供了良好的性能.
- 机器学习模型,特别是极端梯度提升和随机森林,为保险库预测提供了更高的精度.
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