Myopia risk prediction method, device, electronic device and medium

Abstract

The present application relates to the technical field of myopia prevention and control, and in particular to a method, device, electronic device and medium for predicting the risk of myopia. The method comprises obtaining vision examination data of minors in a target area; determining the myopia prevalence of each age in the minors based on the vision examination data; determining the threshold percentile corresponding to each age based on the myopia prevalence; fitting a myopia risk evolution curve corresponding to each age based on the vision examination data and the threshold percentile; and predicting the myopia onset age of the individual to be analyzed based on the myopia risk evolution curve. The present application can predict the myopia evolution of minors and enhance the awareness of parents and children in preventing and controlling myopia.

Description

Technical Field

[0001] The present application relates to the technical field of myopia prevention and control, and in particular to a method, device, electronic device and medium for predicting the risk of myopia. Background Art

[0002] Myopia is the most common type of refractive error. The myopia rate among children and adolescents in East Asia and Southeast Asia is significantly higher than in other parts of the world, and has been rising rapidly in recent decades. my country is located in East Asia, and the situation of myopia prevention and control among children and adolescents is severe. Myopia not only affects the visual experience, but also increases the risk of eye diseases and complications as the degree of myopia increases. Studies have shown that high myopia can lead to eye diseases and diseases such as retinal detachment, macular choroidal degeneration, immature cataracts and glaucoma.

[0003] At present, the main corrective treatment for myopia in children and adolescents is wearing glasses, including frame glasses, orthokeratology lenses and multifocal soft lenses, but this type of optical correction can only delay the progression of myopia. Although a large number of studies have confirmed that intervention measures such as increasing outdoor activities, reducing the time and intensity of close work and electronic screen use, and strengthening eye care can effectively prevent the occurrence of myopia and delay the progression of myopia, the early onset and high incidence of myopia are still severe. This is to a certain extent related to the relatively long latent period of myopia, weak awareness of early prevention and control, and greater difficulty in health education. Mobilizing the subjective initiative of parents and students, strengthening early prevention awareness, and actively staying away from myopia risk factors are the key to myopia prevention and control.

[0004] Regular naked eye distance vision and refractive examinations are important means of dynamically monitoring the occurrence and progression of myopia. However, it is still unclear how to predict the risk of future myopia based on the results of refractive examinations, which has resulted in refractive examinations failing to effectively play a predictive and early warning role. Summary of the invention

[0005] In order to predict the occurrence of myopia in minors and enhance the awareness of parents and children in preventing and controlling myopia, this application proposes a method, device, electronic device and medium for predicting the risk of myopia.

[0006] In the first aspect of the present application, a method for predicting the risk of myopia is proposed, the method comprising obtaining vision examination data of a population of minors in a target area; determining the myopia prevalence of each age in the population of minors based on the vision examination data; determining a cutoff percentile corresponding to each age based on the myopia prevalence; fitting a myopia risk evolution curve corresponding to each age based on the vision examination data and the cutoff percentile; and predicting the myopia onset age of the individual to be analyzed based on the myopia risk evolution curve.

[0007] By adopting the above technical scheme, the vision examination data of the minors in the target area are obtained, and the vision examination data are all vision examination data of the minors collected by the government departments of the target area according to the "Implementation Plan for Comprehensive Prevention and Control of Myopia in Children and Adolescents". The vision examination data are analyzed to determine the myopia prevalence corresponding to each age in the minors, and the value of 100 times the myopia prevalence is used as the boundary percentile corresponding to each age. By using the determined boundary percentile corresponding to each age and the vision examination data, a myopia risk evolution curve corresponding to each age of minors aged 0-18 years old can be fitted, and then the myopia risk evolution curve can be used to predict the myopia age of individuals to be analyzed at different ages. Through the above technical scheme, epidemiological methods are applied to predict the myopia risk of minors from the perspective of the population, so that the individuals to be analyzed can have some understanding of their own myopia occurrence in the future, enhance the awareness of preventing and controlling myopia, and actively produce changes in their thoughts, attitudes and behavioral habits.

[0008] Preferably, the vision test data at least includes age, binocular non-mydriasis optometry results and naked eye distance vision, and determining the prevalence of myopia at each age in the minor population according to the vision test data includes:

[0009] Calculating the equivalent spherical power of each individual in the minor population according to the binocular non-mydriatic optometry results;

[0010] Determine among the minors, individuals whose equivalent spherical power is less than a preset power threshold and whose naked eye far vision is less than a preset far vision threshold as myopic individuals;

[0011] Based on the identified individuals suffering from myopia, the prevalence of myopia at each age in the minor population is calculated.

[0012] Preferably, fitting the myopia risk evolution curve corresponding to each age according to the vision test data and the threshold percentile includes:

[0013] The equivalent spherical diopters are grouped according to age to obtain the equivalent spherical diopters corresponding to each age group in the minor group;

[0014] In each group of equivalent spherical diopters, the percentiles corresponding to the threshold percentiles are respectively extracted;

[0015] According to the percentiles extracted from each group of equivalent spherical diopters and the ages corresponding to the percentiles, myopia age-equivalent spherical diopters curves were fitted respectively to obtain the myopia risk evolution curve corresponding to each age.

[0016] Preferably, the myopia risk evolution curve is:

[0017] Y=b+a1X+a2X 2 +a3X 3

[0018] in,

[0019] a1, a2, a3 and b are all constants;

[0020] Y is the predicted age of myopia;

[0021] X is the equivalent spherical power.

[0022] Preferably, based on the myopia risk evolution curve, predicting the myopia onset age of the individual to be analyzed includes:

[0023] Obtain the age and equivalent spherical power of the individual to be analyzed;

[0024] Determining, according to the age of the individual to be analyzed, a myopia risk evolution curve for predicting the age of myopia onset for the individual to be analyzed;

[0025] The myopia onset age of the individual to be analyzed is predicted based on the determined myopia risk evolution curve and the equivalent spherical diopter of the individual to be analyzed.

[0026] In a second aspect of the present application, a device for predicting the risk of myopia is proposed, the device comprising:

[0027] An acquisition module, used for acquiring vision examination data of minors in a target area;

[0028] A first determination module is used to determine the prevalence of myopia at each age in the minor population according to the vision test data;

[0029] A second confirmation module is used to determine the threshold percentile of each age according to the myopia prevalence rate;

[0030] A fitting module, used for fitting the myopia risk evolution curve corresponding to each age according to the vision test data and the threshold percentile;

[0031] A prediction module is used to predict the myopia onset age of the individual to be analyzed based on the myopia risk evolution curve.

[0032] Preferably, the vision test data at least includes age, binocular non-mydriasis optometry results, and naked eye distance vision, and the first determination module is specifically used to:

[0033] Calculating the equivalent spherical power of each person in the minor group according to the binocular non-mydriatic optometry results;

[0034] Determining among the minors, individuals whose equivalent spherical power is less than a preset power threshold and whose naked eye far vision is less than a preset far vision threshold are individuals suffering from myopia;

[0035] Based on the identified individuals suffering from myopia, the prevalence of myopia at each age in the minor population is determined.

[0036] Preferably, the fitting module is specifically used for:

[0037] The equivalent spherical diopters are grouped according to age to obtain the equivalent spherical diopters corresponding to each age group in the minor group;

[0038] In each group of equivalent spherical diopters, the percentiles corresponding to the threshold percentiles are respectively extracted;

[0039] According to the percentiles extracted from each group of equivalent spherical diopters and the ages corresponding to the percentiles, myopia age-equivalent spherical diopters curves were fitted respectively to obtain the myopia risk evolution curve corresponding to each age.

[0040] In a third aspect of the present application, an electronic device is provided, comprising a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, the method as described in any one of the first aspects is implemented.

[0041] In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method as described in any one of the first aspects is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0043] Figure 1 A structural diagram of an electronic device according to an embodiment of the present application is shown.

[0044] Figure 2 A flow chart of a method for predicting the risk of myopia in an embodiment of the present application is shown.

[0045] Figure 3 The principle block diagram of the myopia risk prediction device in the embodiment of the present application is shown. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] In order to facilitate the understanding of the embodiments of the present application, some terms involved in the embodiments of the present application are first explained.

[0048] Percentile, a statistical term, is about understanding the frequency distribution of a set of data.

[0049] Percentile, a statistical term, sorts a set of data from small to large and calculates the corresponding cumulative percentile. The value of the data corresponding to a certain percentile is called the percentile of this percentile.

[0050] Myopia is the most common type of refractive error. The myopia rate among children and adolescents in East Asia and Southeast Asia is significantly higher than in other parts of the world, and has been rising rapidly in recent decades. my country is located in East Asia, and the situation of myopia prevention and control among children and adolescents is severe. According to a sampling survey conducted by the National Health Commission in 2020, the myopia rate among 6-year-old children in my country is 14.3%, 35.6% among primary school students, 71.1% among junior high school students, and 80.5% among high school students. Myopia not only affects the visual experience, but also increases the risk of eye lesions and complications as the degree of myopia increases. Studies have shown that high myopia can lead to eye lesions and diseases such as retinal detachment, macular choroidal degeneration, immature cataracts and glaucoma.

[0051] At present, the main corrective treatment for myopia in children and adolescents is wearing glasses, including frame glasses, orthokeratology lenses and multifocal soft lenses, but this type of optical correction can only delay the progression of myopia. Although a large number of studies have confirmed that intervention measures such as increasing outdoor activities, reducing the time and intensity of close work and electronic screen use, and strengthening eye care can effectively prevent the occurrence of myopia and delay the progression of myopia, the early onset and high incidence of myopia are still severe. This is to a certain extent related to the relatively long latent period of myopia, weak awareness of early prevention and control, and greater difficulty in health education. Mobilizing the subjective initiative of parents and students, strengthening early prevention awareness, and actively staying away from myopia risk factors are the key to myopia prevention and control.

[0052] Regular naked eye distance vision and refractive examinations are important means of dynamically monitoring the occurrence and progression of myopia. However, it is still unclear how to predict the risk of future myopia based on the results of refractive examinations, which has resulted in refractive examinations failing to effectively play a predictive and early warning role.

[0053] In the paper "Feasibility Study on Screening Refractive Errors in Children Aged 3 to 15 with Non-Mydriatic Optometry", it is pointed out that the average equivalent spherical diopters of each age group before mydriasis show a deepening of negative equivalent spherical diopters with age. After mydriasis, the average equivalent spherical diopters of each age group show a gradual decrease in positive refraction, and then a gradual deepening of negative refraction. On the other hand, genetic factors are fixed, and the percentile of the genetic manifestation of the occurrence and progression of myopia in each individual in the population is basically determined; environmental factors are subjective and changeable, and the impact on the group is normally distributed. From the above paper, it can be seen that the equivalent spherical diopters change continuously, and in the adolescent stage, they show a monotonous and decreasing trend with age. Therefore, with the increase of age, the rate of decline of the equivalent spherical diopters of each individual will be at the average level of the group of that age, and the percentile of the equivalent spherical diopters of the individual at that age will remain stable over time. Based on the above theoretical foundation, the present application proposes a method, device, electronic device and medium for predicting the risk of myopia.

[0054] Next, the system architecture involved in the embodiment of the present application is introduced. It should be noted that the system architecture and business scenarios described in the embodiment of the present application are for the purpose of more clearly explaining the technical solutions of the embodiment of the present application, and do not constitute a limitation on the technical solutions provided in the embodiment of the present application. It is known to those skilled in the art that with the evolution of the network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiment of the present application are also applicable to similar technical problems.

[0055] Figure 1 A structural diagram of an electronic device according to an embodiment of the present application is shown.

[0056] See also Figure 1 , the electronic device 100 includes a processor 101 and a memory 103. The processor 101 and the memory 103 are connected, such as through a bus 102. Optionally, the electronic device 100 may also include a transceiver 104. It should be noted that in actual applications, the transceiver 104 is not limited to one, and the structure of the electronic device 100 does not constitute a limitation on the embodiments of the present application.

[0057] The processor 101 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 101 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0058] The bus 102 may include a path to transmit information between the above components. The bus 102 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 102 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 1 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0059] The memory 103 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0060] The memory 103 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 101. The processor 101 is used to execute the application code stored in the memory 103 to implement the myopia risk prediction method.

[0061] The electronic devices include but are not limited to: mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), etc., and fixed terminals such as digital TVs, desktop computers, etc. It should be noted that: Figure 1 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0062] Figure 2 The flowchart of the method for predicting the risk of myopia in the embodiment of the present application is shown in FIG. Figure 2 , the method comprises:

[0063] Step S201, obtaining vision examination data of minors in the target area.

[0064] In the embodiments of the present application, the target area can be selected as a certain city, a certain province or a national area. Specifically, the target area is selected based on actual analysis needs. The source of the vision examination data is the "Implementation Plan for Comprehensive Prevention and Control of Myopia in Children and Adolescents" designated by the Ministry of Education, the National Health Commission and other eight departments. The government departments in the target area implement vision examinations for minors in accordance with the above plan, and use optometrists or vision screeners to conduct vision examinations on minors at regular intervals and at fixed locations. The vision examination data in this application can be obtained in the local government system. The vision examination data of all minors in the target area. In other application embodiments, the vision examination data of minors in preset age groups can also be obtained.

[0065] In some application embodiments, the vision test data includes at least age, binocular non-mydriatic optometry results, and naked eye distance vision, wherein the binocular non-mydriatic optometry results include spherical power (DS), cylindrical power (DC), and axis position.

[0066] Step S202, determining the prevalence of myopia at each age in the minor population based on the vision examination data.

[0067] In some application embodiments, determining the prevalence of myopia at each age in the underage population based on vision examination data is achieved by the following steps.

[0068] Step A1, calculating the equivalent spherical power of each individual in the minor population according to the non-mydriatic optometry results of both eyes.

[0069] In step A1, the formula for calculating the equivalent spherical power according to the binocular non-mydriatic optometry results is: equivalent spherical power (SE) = spherical power (DS) + 1 / 2 * cylindrical power (DC). Based on the binocular non-mydriatic optometry results in the vision test data obtained in step S201, the equivalent spherical power of each individual in the minor population in the target area is calculated using the above formula.

[0070] Step A2, determining among minors, individuals whose equivalent spherical power is less than a preset power threshold and whose naked eye far vision is less than a preset far vision threshold as myopic individuals.

[0071] Based on the equivalent spherical degree calculated in step A1 and the naked eye far vision in the visual acuity test data, analyze whether each individual in the minor population is myopic. The standard for analyzing whether it is myopic is to determine whether the equivalent spherical degree of the individual is less than a preset degree threshold and whether the corresponding naked eye far vision is less than a preset far vision threshold. The preferred value of the preset degree threshold is 5.0, and the preferred value of the preset far vision threshold is -0.50D. When the equivalent spherical degree is less than -0.50D and the naked eye far vision is less than 5.0, it can be determined that the individual is a myopic individual. In a feasible manner, after determining the myopic individuals in the minor population, the myopic individuals are labeled with myopia to facilitate the subsequent use of the data.

[0072] Step A3, calculating the myopia prevalence rate of each age group in the minor population based on the determined myopia-affected individuals.

[0073] The myopic individuals determined in step A2 are counted according to their ages to obtain the number of myopic individuals corresponding to each age. Based on the total number of individuals corresponding to each age in the vision examination data and the number of myopic individuals corresponding to each age, the myopia prevalence rate corresponding to each age is calculated using the method of myopia prevalence rate = number of myopic individuals / total number of individuals*100%.

[0074] Step S203, determining the threshold percentile corresponding to each age group according to the myopia prevalence rate.

[0075] In the embodiment of the present application, the threshold percentile is the myopia prevalence multiplied by 100. The myopia prevalence corresponding to each age in the minor population in the target area determined in step S202 can be used to obtain the threshold percentile corresponding to each age. In one example, the obtained vision examination data includes vision examination data for people aged 1, 2, 3, ... 18. Then, through step S202, it can be obtained that the myopia prevalence corresponding to each age is p1, p2, p3, ... p 18, then the threshold percentiles corresponding to each age are P1=p1*100, P2=p2*100, P3=p3*100, ..., P 18 =p 18 *100.

[0076] In the embodiments of the present application, the cutoff percentile indicates the percentile at which myopia is expected to occur in the distribution of equivalent spherical diopters for each age. In the distribution of equivalent spherical diopters corresponding to each age, the percentile corresponding to each age, i.e., the equivalent spherical diopters, can be obtained based on the cutoff percentile.

[0077] Step S204, fitting the myopia risk evolution curve corresponding to each age group according to the vision test data and the cut-off percentile.

[0078] In some application embodiments, fitting the myopia risk evolution curve corresponding to each age according to the vision test data and the threshold percentile includes the following steps:

[0079] Step B1, grouping the equivalent spherical diopters according to age, and obtaining the equivalent spherical diopters corresponding to each age group in the minor population.

[0080] The equivalent spherical diopters of each individual in the minor population in the target area calculated in step A1 are grouped according to age to obtain the equivalent spherical diopters corresponding to each age. In one example, if the obtained vision test data includes vision test data of minor population aged 7-18 in the target area, then after the above steps, a group of equivalent spherical diopters corresponding to 7 years old, a group of equivalent spherical diopters corresponding to 8 years old, ..., a group of equivalent spherical diopters corresponding to 18 years old can be obtained respectively.

[0081] Step B2, in each group of equivalent spherical diopters, extract the percentiles corresponding to the threshold percentiles.

[0082] In step S203, the threshold percentiles corresponding to different ages have been obtained, and the percentiles corresponding to each threshold percentile in the equivalent spherical diopters of each group are extracted, that is, the equivalent spherical diopters corresponding to each threshold percentile, to obtain a group of percentiles corresponding to each age. In one example, the acquired vision collection data includes vision examination data of a minor group aged 1-i, and the threshold percentiles P1, P2, P3, ..., P4, ..., P5, ..., P6, ..., P7, ..., P8, ..., P9, ..., P10, ..., P11, ..., P12, ..., P13, ..., P14, ..., P15, ..., P16, ..., P17, ..., P18, ..., P19, ..., P20, ..., P21, ..., P22, ..., P23, ..., P24, ..., P25, ..., P26, ..., P27, ..., P28, ..., P29, ..., P30, ..., P31, ..., P32, ..., P33, ..., P34, ..., P35, ..., P36, ..., P37, ..., P38, ..., P39, ..., P40, ..., P41, ..., P42, ..., P43, ..., P44, ..., P45, ..., P46, ..., P47, ..., P48, ..., P49, ..., P50, ..., P51, ..., P52, ..., P53, ..., P54, ..., P55, ..., P56, ..., P57, ..., P58, ..., P59, ..., P60, ..., P61, ..., P62, ..., P63, ..., P64, ..., P65, ..., P66, ..., P67, ..., P68, ... i , then the percentile extraction in the equivalent spherical diopters distribution corresponding to 7 years old can obtain the equivalent spherical diopters SE corresponding to the P1th percentile 71 , P2th percentile equivalent spherical power SE 71 ……、P iPercentile spherical equivalent SE 7i . The following is available in SE ij Indicates that age i is in the Pth j Percentile spherical equivalent power.

[0083] Step B3, according to the percentiles extracted from each group of equivalent spherical diopters and the ages corresponding to the percentiles, respectively fit the myopia age-equivalent spherical diopters curve to obtain the myopia risk evolution curve corresponding to each age.

[0084] The percentiles extracted from the equivalent spherical diopter corresponding to each age in step B2 are used as independent variables. When obtaining the cutoff percentiles, the age corresponding to each cutoff percentile is used as the dependent variable. A myopia age-equivalent spherical diopter curve is fitted for each group of percentiles, and the curve is used as the myopia risk evolution curve for the age corresponding to the group of percentiles.

[0085] In some application embodiments, the expression of the myopia risk evolution curve is:

[0086] Y=b+a1X+a2X 2 +a3X 3

[0087] Among them, a1, a2, a3 and b are all constants; Y is the predicted age of myopia; X is the equivalent spherical power.

[0088] In one example, the vision examination data of minors aged 7-13 in a county in Shandong Province is taken as an example. The age of each individual in the minor population when undergoing the vision examination is used as the classification basis, the age of myopia Y is predicted as the dependent variable, and the equivalent spherical power at the time of the examination is used as the independent variable to fit the age-equivalent spherical power curve. See Table 1, and the myopia risk evolution curve equation for different ages can be obtained.

[0089]

[0090]

[0091] Table 1. Age-myopia risk evolution curve equation

[0092] In other application embodiments, a binary quartic equation or a binary quadratic equation of age-equivalent spherical diopters may be fitted. The optimal curve expression in the embodiment of the present application is a binary cubic equation of age-equivalent spherical diopters. In the present application, the binary cubic equation can cover more points composed of age and equivalent spherical diopters, and has the highest accuracy.

[0093] Step S205, predicting the myopia onset age of the individual to be analyzed based on the myopia risk evolution curve.

[0094] In some application embodiments, the age and equivalent spherical diopter of the individual to be analyzed are obtained; based on the age of the individual to be analyzed, a myopia risk evolution curve for predicting the age of myopia in the individual to be analyzed is determined; based on the determined myopia risk evolution curve and the equivalent spherical diopter of the individual to be analyzed, the age of myopia in the individual to be analyzed is predicted.

[0095] Preferably, the individuals to be analyzed are selected as underage individuals in the same area as the target area in this application, and other areas with similar myopia conditions can also be selected. The current age of the individual to be analyzed at the time of analysis and the equivalent spherical diopter obtained by the current test are obtained, and the myopia risk evolution curve equation corresponding to the age is determined in the age-myopia risk evolution curve equation table according to the age of the individual to be analyzed. The equivalent spherical diopter of the individual to be analyzed is brought into the determined equation, and the value of the predicted myopia age Y can be obtained, that is, the predicted myopia age of the individual to be analyzed. In one example, a 7-year-old underage individual in a county in Shandong Province is selected as the individual to be analyzed. Through vision testing, the current equivalent spherical diopter of the individual to be analyzed is obtained to be 0.13D, and the current age of the individual to be analyzed is 7 years old, so the myopia risk evolution curve equation Y corresponding to 7 years old in Table 1 is selected = 12.9744 + 9.5178X + 8.4333X 2 +3.7473X 3 , substituting the equivalent spherical power of the individual to be analyzed, 0.13D, into the equation, we get the value of Y which is approximately 14.3624 years old. Therefore, it can be concluded that the individual to be analyzed is expected to develop myopia between the ages of 14 and 15. The prediction results can be used to remind the individual to be analyzed, so that the individual to be analyzed can understand his or her myopia condition, mobilize subjective initiative, strengthen prevention and control, and reduce the chance of myopia.

[0096] Based on the existing theoretical foundation, as the age increases, the rate of decline of the individual's equivalent spherical power will be at the average level of the group of the same age, and the individual's equivalent spherical power is located at the percentile of the same age and remains stable over time. Therefore, the current equivalent spherical power of the individual to be analyzed is substituted into the myopia risk evolution curve equation corresponding to its age. In essence, it is predicted that the current equivalent spherical power of the individual is located in the hundredth percentile of the equivalent spherical power of the same age. The corresponding Y of the percentile in the curve is the predicted age of myopia of the individual, and the percentile is the boundary percentile corresponding to the Y age. It is concluded that when the individual to be analyzed reaches the age of Y, the equivalent spherical power of the individual to be analyzed is just at the boundary percentile in the distribution of the equivalent spherical power of the age of Y, reaching the boundary value of the predicted myopia occurrence at that age. It can be predicted that when the individual to be analyzed reaches the age of Y, he may suffer from myopia. This application applies epidemiological methods to analyze based on the vision examination data of the population to predict the occurrence of myopia in minors. The myopia risk evolution curve constructed in this application has a wide range of applications, is simple to operate, and is easy to use.

[0097] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present disclosure is not limited by the order of the actions described, because according to the present disclosure, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present disclosure.

[0098] The above is an introduction to the method embodiment. The following is a further explanation of the scheme disclosed in the present invention through an apparatus embodiment.

[0099] Figure 3 FIG. 1 is a schematic diagram showing a device for predicting myopia risk according to an embodiment of the present invention. Figure 3 As shown, the device comprises:

[0100] The acquisition module 301 is used to acquire vision examination data of minors in the target area.

[0101] The first determination module 302 is used to determine the myopia prevalence rate of each age group in the minor population according to the vision examination data.

[0102] The second confirmation module 303 is used to determine the threshold percentile of each age according to the myopia prevalence rate.

[0103] The fitting module 304 is used to fit the myopia risk evolution curve corresponding to each age based on the vision test data and the threshold percentile.

[0104] The prediction module 305 is used to predict the myopia onset age of the individual to be analyzed based on the myopia risk evolution curve.

[0105] In some application embodiments, the vision test data includes at least age, binocular non-mydriasis optometry results, and naked eye distance vision, and the first determination module is specifically used to:

[0106] The equivalent spherical power of each person in the minor population was calculated based on the non-mydriatic optometry results of both eyes;

[0107] Determine among the minors that individuals whose equivalent spherical power is less than a preset power threshold and whose naked eye distance vision is less than a preset distance vision threshold are myopic individuals;

[0108] Based on the individuals identified as having myopia, the prevalence of myopia at each age in the minor population was determined.

[0109] In some application embodiments, the fitting module is specifically used for:

[0110] The equivalent spherical diopters are grouped according to age, and the equivalent spherical diopters corresponding to each age group in the minors are obtained;

[0111] In each group of equivalent spherical diopters, the percentiles corresponding to the cutoff percentiles were extracted;

[0112] According to the percentiles extracted from each group of equivalent spherical diopters and the ages corresponding to the percentiles, the age-equivalent spherical diopters curves were fitted respectively to obtain the myopia risk evolution curve corresponding to each age.

[0113] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0114] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0115] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0116] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for predicting the risk of myopia, characterized in that: include: Obtain vision examination data of minors in target areas; Determining the prevalence of myopia at each age in the minor population based on the vision examination data; Determine the cutoff percentile corresponding to each age based on the myopia prevalence rate; the cutoff percentile is the percentile at which the cutoff value of myopia is expected to occur in the distribution of equivalent spherical diopters at each age, and the cutoff percentile is calculated by multiplying the myopia prevalence rate by 100; Fitting a myopia risk evolution curve corresponding to each age group according to the vision test data and the threshold percentile; Based on the myopia risk evolution curve, predicting the age of myopia onset of the individual to be analyzed; According to the visual acuity test data and the threshold percentile, fitting the myopia risk evolution curve corresponding to each age, including: Grouping the equivalent spherical diopters according to age to obtain the equivalent spherical diopters corresponding to each age group in the minor group; In each group of equivalent spherical diopters, the percentiles corresponding to the threshold percentiles are respectively extracted; According to the percentiles extracted from each group of equivalent spherical diopters and the ages corresponding to the percentiles, myopia age-equivalent spherical diopters curves are fitted respectively to obtain the myopia risk evolution curve corresponding to each age; The myopia risk evolution curve is: Y=b+a1X+a2X 2 +a3X 3 in, a1, a2, a3 and b are all constants; Y is the predicted age of myopia; X is the equivalent spherical power; Based on the myopia risk evolution curve, predicting the age of myopia onset of the individual to be analyzed includes: Obtain the age and equivalent spherical power of the individual to be analyzed; Determining, according to the age of the individual to be analyzed, a myopia risk evolution curve for predicting the age of myopia onset for the individual to be analyzed; The myopia onset age of the individual to be analyzed is predicted based on the determined myopia risk evolution curve and the equivalent spherical diopter of the individual to be analyzed.

2. The method for predicting myopia risk according to claim 1, characterized in that: The vision test data at least includes age, binocular non-mydriasis optometry results and naked eye distance vision, and the myopia prevalence rate of each age group in the minor population is determined based on the vision test data, including: Calculating the equivalent spherical power of each individual in the minor population according to the binocular non-mydriatic optometry results; Determine among the minors, individuals whose equivalent spherical power is less than a preset power threshold and whose naked eye far vision is less than a preset far vision threshold as myopic individuals; Based on the identified individuals suffering from myopia, the prevalence of myopia at each age in the minor population is calculated.

3. A device for predicting the risk of myopia, characterized in that: include: An acquisition module, used for acquiring vision examination data of minors in a target area; A first determination module is used to determine the prevalence of myopia at each age in the minor population according to the vision test data; A second confirmation module is used to determine a threshold percentile for each age based on the myopia prevalence rate; the threshold percentile is the percentile at which the threshold value of myopia is expected to occur in the distribution of equivalent spherical diopters at each age, and the threshold percentile is calculated by multiplying the myopia prevalence rate by 100; A fitting module, used for fitting the myopia risk evolution curve corresponding to each age according to the vision test data and the threshold percentile; A prediction module, used to predict the myopia onset age of the individual to be analyzed based on the myopia risk evolution curve; The fitting module is specifically used for: Grouping the equivalent spherical diopters according to age to obtain the equivalent spherical diopters corresponding to each age group in the minor group; In each group of equivalent spherical diopters, the percentiles corresponding to the threshold percentiles are respectively extracted; According to the percentiles extracted from each group of equivalent spherical diopters and the ages corresponding to the percentiles, myopia age-equivalent spherical diopters curves are fitted respectively to obtain the myopia risk evolution curve corresponding to each age; The myopia risk evolution curve is: Y=b+a1X+a2X 2 +a3X 3 in, a1, a2, a3 and b are all constants; Y is the predicted age of myopia; X is the equivalent spherical power; Based on the myopia risk evolution curve, predicting the age of myopia onset of the individual to be analyzed includes: Obtain the age and equivalent spherical power of the individual to be analyzed; Determining, according to the age of the individual to be analyzed, a myopia risk evolution curve for predicting the age of myopia onset for the individual to be analyzed; The myopia onset age of the individual to be analyzed is predicted based on the determined myopia risk evolution curve and the equivalent spherical diopter of the individual to be analyzed.

4. The myopia risk prediction device according to claim 3, characterized in that: The vision test data at least includes age, binocular non-mydriasis optometry results, and naked eye distance vision, and the first determination module is specifically used for: Calculating the equivalent spherical power of each person in the minor group according to the binocular non-mydriatic optometry results; Determining that among the minors, individuals whose equivalent spherical power is less than a preset power threshold and whose naked eye far vision is less than a preset far vision threshold are myopic individuals; Based on the identified individuals suffering from myopia, the prevalence of myopia at each age in the minor population is determined.

5. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the program, the method according to any one of claims 1 to 2 is implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 2 is implemented.

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