Prediction method of diopter based on sequence of ocular biological parameters
10.3760/cma.j.cn121382-20240428-00501
- VernacularTitle:基于眼生物参数序列的屈光度预测方法研究
- Author:
Luebiao XU
1
;
Lan DING
;
Chen LIANG
;
Yuliang WANG
;
Yujia LIU
;
Jianmin SHANG
;
Jun ZHU
;
Huazhong XIANG
;
Renyuan CHU
;
Cheng WANG
;
Xiaomei QU
Author Information
1. 上海理工大学健康科学与工程学院，医用光学技术与仪器教育部重点实验室，生物医学光学与视光学研究所，上海 200093
- Keywords:
Myopia;
Ocular biological parameters;
Diopter;
Least square method;
Back propagation neural network
- From:
International Journal of Biomedical Engineering
2024;47(5):417-422
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish a prediction method of diopter based on sequence of ocular biological parameters.Methods:A stratified random cluster sampling method was used to extract the dataset. The dataset consisted of data collected from January 2022 to January 2023 by the Eye & ENT Hospital, Fudan University, from children aged 5 to 13 years in 2 key schools and 2 general schools of Yangpu District, Shanghai. Children’s ocular biological parameters, including sex, age, diopter, axial length, corneal curvature, and anterior chamber depth were collected. The slope of the optimally fitted straight line was calculated using the least squares method. The least square-back propagation (BP) neural network model was established by combining baseline data and the pre-processed rate of the change of ocular biological parameters. The dataset was divided into the training set and the validation set according to the ratio of 8:2 for five-fold cross-validation. The model performance was evaluated by using the mean absolute error (MAE), mean squared error (MSE), root mean square error (RMSE), correlation coefficient R, and coefficient of determination R2. Results:The optimal performances of R2, R, RMSE, MAE, and MSE of the least square-BP neural network model were 0.96, 0.981 9, 0.214 2, 0.139 9 D, 0.045 9, respectively. The regression equation between the predicted value and the true value of the diopter was y=0.97 x+ 0.014 8, R2=0.97, with good correlation. In the internal verification, MAE values of the diopter at three, six, nine, and twelve months of follow-up were 0.110 1, 0.136 0, 0.153 7, and 0.184 8 D, respectively, which achieved clinically acceptable performance (less than 0.25 D). In the external validation, the errors were less than 0.25 D at all ages. Conclusions:A prediction method of diopter based on sequence of ocular biological parameters was successfully developed.
