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Effect of vault on predicting postoperative refractive error for posterior chamber phakic intraocular lens based on a machine learning model.

Yinjie JiangYang ShenLin WangXun ChenJing TangXing-Tao ZhouTong MaLie JuYuzhong ChenB Zongyuan GeXingtao ZhouXiaoying Wang
Published in: Journal of cataract and refractive surgery (2023)
Our random forest-based calculator, considering vault and variable ocular parameters, illustrated superiority over the existing calculator on our datasets. Choosing an appropriate lens size to control the vault within the ideal range is helpful to avoid refractive surprises.
Keyphrases
  • machine learning
  • cataract surgery
  • climate change
  • patients undergoing
  • artificial intelligence
  • big data