儿童青少年视力防控预测数据
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学校学生视力筛查后平台根据算法对学生1年、3年、5年以及10年后的视力进行预测。可用作预测n年后一部分人群的视力状况；也可为相关课题研究提供相应数据。收集不同省份（浙江、福建、内蒙古、河南、河北、山西、黑龙江等等）不同年龄段（集中在3-18岁）的180万视力基础数据，保证数据的完整性、准确性以及代表性。 算法规则：视力预估值 = β0 + β1*X1 + β2*X2 + β3*X3 + β4*X4。 式中：X1表示当前学生年龄，X2表示学生性别（男 1，女 0），X3表示学生当前视力值，X4表示预测的天数(1年：365*1、3年：365*3、5年：365*5、10年：365*10)； β0、β1、β2、β3、β4 根据上述180万数据求得回归系数。 学生每次检测的时候根据当时 性别、年龄、视力数据等等预测该学生1年、3年、5年、10年后视力的预估值。
Following vision screening for school students, the platform employs an algorithm to predict the students' visual acuity at 1, 3, 5, and 10 years post-screening. This dataset can be utilized to forecast the visual status of a subset of the population after n years, and also supply pertinent data for relevant research endeavors. It collects 1.8 million sets of basic vision-related data from students aged primarily 3 to 18 years across multiple provinces including Zhejiang, Fujian, Inner Mongolia, Henan, Hebei, Shanxi, Heilongjiang, and others, with guaranteed data integrity, accuracy, and representativeness. Algorithm rule: Predicted visual acuity = β0 + β1*X1 + β2*X2 + β3*X3 + β4*X4. In this formula: X1 denotes the student's current age; X2 represents the student's gender (male = 1, female = 0); X3 stands for the student's current visual acuity value; X4 refers to the number of days corresponding to the prediction period (1 year: 365*1, 3 years: 365*3, 5 years: 365*5, 10 years: 365*10); β0, β1, β2, β3, β4 are regression coefficients derived from the aforementioned 1.8 million datasets. During each student's examination, the predicted visual acuity values for 1, 3, 5, and 10 years later can be calculated based on the student's current gender, age, visual acuity data and other relevant information.
