FindTrial
Sign In

Applying Machine Learning Techniques in Nomogram Prediction and Analysis for SMILE Treatment

Applying Machine Learning Techniques in Nomogram Prediction and Analysis for SMILE Treatment

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR1900024875
Enrollment
Unknown
Registered
2019-08-01
Start date
2017-07-25
Completion date
Unknown
Last updated
2019-08-27

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

Conditions

refractive surgery

Interventions

Group 2:machine learning technique for prediction of small incision lenticule extraction(SMILE) nomogram
Group 1:Ophthalmologist operation

Sponsors

Tianjin Eye Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. aged 18 to 45 years; 2. spherical myopia up to -9.00D, and myopic astigmatism up to -3.00D; 3. corrected distance visual acuity (CDVA) of 20/40 or better; 4. postoperative residual stromal bed thickness > 250um; 5. stable refraction for more than 2 years.

Exclusion criteria

Exclusion criteria: 1) corneal disease; 2) ocular trauma; 3) suspicion of keratoconus on corneal topography. Patients were required to stop wearing soft contact lenses for at least 2 weeks and rigid contact lenses for at least 4 weeks before examination.

Design outcomes

Primary

MeasureTime frame
BCVA preopertiva;preoperation refraction;UDVA preoperative;BCVA postoperation;refraction postoperation;UDVA postoperation;—

Countries

China

Contacts

Public ContactWang Yan

Tianjin Eye Hospital

wangyan7143@vip.sina.con+86 13602089393

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026