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Predicting Small Effective Optical Zone After SMILE via Multimodal Machine Learning Integrating Corneal Topography

Jian Xiong1,2, Weihao Gao3, Fei Huang1

  • 1Ophthalmic Center, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.

Translational Vision Science & Technology
|February 20, 2026
PubMed
Summary

A new machine learning model accurately predicts small effective optical zones (EOZ) after small incision lenticule extraction (SMILE). This AI tool aids surgeons in preoperative planning for better patient outcomes.

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Area of Science:

  • Ophthalmology
  • Medical Artificial Intelligence
  • Corneal Surgery

Background:

  • Small incision lenticule extraction (SMILE) is a popular refractive surgery.
  • Predicting the effective optical zone (EOZ) is crucial for optimizing visual outcomes.
  • Accurate preoperative prediction of small EOZ (<5.5 mm) remains a challenge.

Purpose of the Study:

  • To develop and validate a machine learning system for predicting small effective optical zone (EOZ) after SMILE.
  • To assess the system's performance using multimodal preoperative data.

Main Methods:

  • A multicenter cohort study involving 1030 eyes undergoing SMILE.
  • Development of the AACM-PP-Model integrating anterior corneal curvature maps (AACM) and preoperative parameters (PP).
  • Comparison against parameter-only and image-only models using AUROC and macro F1 score.

Main Results:

  • The AACM-PP-Model achieved high performance (AUROC 0.897, macro F1 0.823) in primary validation.
  • It outperformed parameter-only and image-only models in internal and external test sets.
  • Intraoperative frame models showed poor predictive performance.

Conclusions:

  • Multimodal machine learning using standard preoperative data accurately predicts small post-SMILE EOZ.
  • The developed model demonstrates superior generalization for preoperative decision-making.
  • Objective risk stratification supports personalized surgical planning and patient expectation management.