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AI could replace eye drops for measuring nearsightedness

NCT ID NCT07690813

Recruiting now Diagnosis Sponsor: Second Affiliated Hospital of Nanchang University Source: ClinicalTrials.gov ↗

First seen Jul 08, 2026 · Last updated Jul 10, 2026 · Updated 2 times

Summary

This study tests a machine learning model that predicts how much nearsightedness a person has without using dilating eye drops. The model uses standard eye measurements like autorefraction and corneal shape. If accurate, it could make eye exams quicker and more comfortable for adults with myopia.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance
Machine learning model for predicting cycloplegic refraction
What this could lead to
If successful, this could make eye exams faster and more comfortable by reducing the need for dilating drops, while still accurately identifying patients who need them.
What could go wrong
The model may not be accurate enough for all patients, and it is tested only in adults with specific degrees of myopia, so results may not apply to everyone.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

eye accommodation disease myopia refractive error

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

ACCOMMODATION CYCLOPLEGIC REFRACTION REFRACTIVE ERRORS

Contacts and locations

Study contacts

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••

Locations

  • The Second Affiliated Hospital of Nanchang University, Nanchang, JiangXi 330000

    RECRUITING

    Jiangxi, China

    Contact Phone: •••-•••-•••• Email: •••••@•••••

    Contact Phone: •••-•••-•••• Email: •••••@•••••

More trials for these conditions

Other studies related to the condition(s) this trial covers.