To explore the prediction of OBL by deep learning model in SMILE surgery

The DL model was used to predict the OBL area during SMILE surgery by identifying the corneal full-view images before laser scanning. The DL model developed may assist surgeons to predict the possible OBL area of patients in advance, so as to adjust some surgical parameters and reduce the formation of OBL, which can avoid negative effects on surgeons' operation and patients' postoperative visual recovery, which has important practical significance.

Inclusion Criteria:

• A condition in which the spherical equivalent refractive error of an eye is ≤ -0.50 D when ocular accommodation is relaxed;
• Age ≥18 years;
• Spherical equivalent (SE) ≥ -10.0D;
• Corrected distance visual acuity (CDVA) ≥ 16/20;
• Stable myopia for at least 2 years;
• No contact lenses wearing for at least 2 weeks

Exclusion Criteria:

• The presence or history of eye conditions other than myopia and astigmatism, such as keratoconus or external eye injury;
• A history of eye surgery;
• The presence or history of systemic diseases.

Patients from clinics in ophthalmic center of the second Affiliated Hospital of Nanchang University