The Second Affiliated Hospital of Nanchang University
Nanchang, Jiangxi, 330000, China
NCT Number: NCT06577012
To explore the prediction of OBL by deep learning model in SMILE surgery
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Notify Me18 year–45 year
All sexes
Observational
Nanchang, Jiangxi, 330000, China
The DL model was used to predict the OBL area during SMILE surgery by identifying the corneal full-view images before laser scanning. The DL model developed may assist surgeons to predict the possible OBL area of patients in advance, so as to adjust some surgical parameters and reduce the formation of OBL, which can avoid negative effects on surgeons' operation and patients' postoperative visual recovery, which has important practical significance.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Small incision lenticule extraction surgeries performed by two Refractive surgery experts (Refractive surgery expert 1: YYF, Associate Professor with 10 years of experience as a refractive surgeon; Refractive surgery expert 2: GF, Associate Professor with 5 years of experience as a refractive surgeon) and a Attending ophthalmologist (XJ, Attending ophthalmologist with 1 year of experience as a refractive surgeon).
Time frame: Day 0
The area of patients with opaque bubble layer were observed during the SMILE surgeries.
Time frame: Day 0
Predictive performance of deep learning model on the OBL in SMILE surgeries.
Time frame: Day 0
Predictive performance of ResNet model on the OBL in SMILE surgeries.
Time frame: Day 0
Predictive performance of Vgg model on the OBL in SMILE surgeries.
Time frame: Day 0
Predictive performance of U-net model on the OBL in SMILE surgeries.
Second Affiliated Hospital of Nanchang University
Other
Predicting an Opaque Bubble Layer During Small-Incision Lenticule Extraction Surgery Based on Deep Learning
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