DL Models Predicting Cycloplegic Refractive Error Based on Non-Cycloplegic Parameters in Myopic Adults

This study presents a machine learning model that predicts cycloplegic refraction in adults with myopia using standard non-cycloplegic eye measurements, aiming to reduce the need for cycloplegic drops while still identifying patients who require them.

Inclusion Criteria: 1. Age 18 to 60 years, of either sex; 2. Spherical equivalent between -0.50 diopters and -10.00 diopters, with myopia in one or both eyes, and with cylinder of 4.00 diopters or less; 3. Best-corrected visual acuity of 20/25 or better in each eye; 4. Clear cornea, no keratoconus, corneal scarring, or other pathologies; clear lens; 5. Intraocular pressure of 21 mmHg or less, with no history of glaucoma; 6. No history of ocular surgery, especially corneal refractive surgery or cataract surgery; 7. Time interval between non-cycloplegic refraction and cycloplegic refraction of 7 days or less, with complete data. Exclusion Criteria: 1. Incomplete clinical data to support the diagnosis; 2. Ocular conditions such as subclinical keratoconus, keratoconus, or moderate-to-severe corneal haze or leukoma; 3. Allergy or contraindication to cycloplegic agents; 4. Refusal to participate in the study.