Prediction of Phakic Intraocular Lens Vault Using Machine Learning.

Prediction of Phakic Intraocular Lens Vault Using Machine Learning. - Prediction of Phakic IOL Vault Using Machine Learning.

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000040934

Enrollment

200

Registered

2020-08-01

Start date

2020-08-01

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Refractive errors

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: unsatisfactory correction with spectacles or contact lenses, 20 to 50 years, stable refraction for at least 3 months, -3.00 to -14.0 diopters (D) of myopia with astigmatism of 3 D or less, anterior chamber depth 2.8 mm or more, endothelial cell density 1800 cells/mm2 or more, and no history of ocular surgery, corneal diseases, cataract, glaucoma or uveitis.

Exclusion criteria

Exclusion criteria: keratoconus

Design outcomes

Primary

Measure	Time frame
Phakic Intraocular Lens Vault	—

Countries

Japan

Contacts

Public ContactKazutaka Kamiya

Kitasato University School of Allied Health Sciences

kamiyak-tky@umin.ac.jp0427788464

Outcome results