Data Collecting
Conditions
Keywords
artificial intelligence, deep learning, cataract surgery, acuity vision, macular, optical coherence tomography
Brief summary
The purpose of this study is to collect the macular OCT images and preoperative and postoperative visual acuity of cataract patients who had been operated in the eye center of the Second Affiliated Hospital of Zhejiang University Medical College, and to train a model that can relatively accurately predict the postoperative visual acuity of patients by deep learing.
Interventions
None listed
Sponsors
Second Affiliated Hospital, School of Medicine, Zhejiang University
Study design
Observational model
OTHER
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
50 Years to 90 Years
Healthy volunteers
Yes
Inclusion criteria
* Senile cataract patients, with or without macular disease, the impact of cataract on vision has affected the daily life of patients.
Exclusion criteria
* Glasses can obviously improve eyesight * In addition to macular disease, combined with other eye diseases that seriously affect vision, resulting in no significant improvement in postoperative vision * Complicated cataract surgery due to trauma and other reasons * Combined with other eye diseases not suitable for intraocular lens implantation * Patients with systemic diseases who cannot tolerate surgery
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Uncorrected distance visual acuity | 1 month postoperatively | The UCVA was measured by the same optometrist at each visit |
| Best Corrected Visual Acuity | 1 month postoperatively | The BCVA was measured by the same optometrist at each visit |
| Macular optical coherence tomography | 1 month postoperatively | Macular oct was measured by the same doctor at each visit |
Countries
China
Contacts
Primary ContactWen Xu
Outcome results
None listed