KR102660560B1 - Method and device for providing cardiovascular risk assessment service - Google Patents

Abstract

A method of providing a cardiovascular risk assessment service performed by at least one processor according to the present disclosure includes the steps of registering examination data from a customer terminal through a health management service; Classifying a plurality of cardiovascular data extracted from the examination data according to risk factor items; Quantifying the target risk for each risk factor item for each cardiovascular data based on a preset risk quantification model; Deriving target information for each risk factor item using the target risk and standard target table for each risk factor item; Predicting information on the age of cardiovascular occurrence based on an approximation between the target absolute risk calculated according to the target risk for each risk factor item and the average absolute risk determined according to the customer information; And providing health management information so that target risk for each risk factor item, target information for each risk factor item, and age information for cardiovascular and cerebrovascular events can be confirmed on the customer terminal through the health care service.

Description

Method and device for providing cardiovascular risk assessment service {METHOD AND DEVICE FOR PROVIDING CARDIOVASCULAR RISK ASSESSMENT SERVICE}

This disclosure relates to a method and device for providing cardiovascular risk assessment services. Specifically, it is about an evaluation technology that can predict information on the age of cardiovascular occurrence according to cardiovascular risk.

Cardiovascular disease is a disease that occurs in the heart and major arteries. Heart disease includes congenital heart disease that occurs at birth and acquired heart disease that develops throughout life. The structure of the heart consists of the heart muscle, cardiovascular vessels, valves, and organs responsible for the heart's electrical signals. Just as it can be divided by the conduction system, heart disease can also be classified into diseases that occur in each region.

Major vascular diseases are diseases in which major arteries such as the aorta, pulmonary artery, carotid artery, cerebral artery, renal artery, and lower extremity artery are blocked, stretched, or ruptured, causing bleeding.

According to statistics on causes of death published by the National Statistical Office in 2009, circulatory system diseases, including hypertensive diseases, ischemic heart diseases, and cerebrovascular diseases, are the second leading cause of death in Korea, after malignant tumors, and for men over 55 years of age. , the mortality rate of circulatory system diseases increases significantly in women over the age of 65. Risk factors related to cardiovascular disease, especially atherosclerosis, are age (middle-aged or older), gender (male), high blood pressure, hyperlipidemia, diabetes, smoking, lack of exercise, and obesity. Major cardiovascular diseases include high blood pressure, ischemic heart disease, coronary artery disease, angina pectoris, myocardial infarction, arteriosclerosis, cerebrovascular disease, stroke, and arrhythmia.

In particular, when the winter weather suddenly becomes cold, the risk of cardiovascular diseases such as angina pectoris, myocardial infarction, and stroke, which includes cerebral hemorrhage and cerebral infarction, increases. If you wake up from a warm bed and are suddenly exposed to cold morning air, the risk of cardiovascular disease increases, so you must take care of your health.

Accordingly, efforts are being made to prevent cardiovascular disease through technology that predicts risk data related to cardiovascular disease.

Republic of Korea Patent Publication No. 10-2016-0086730

The purpose of the present disclosure is to provide a cardiovascular risk assessment service that can predict information on the age of cardiovascular occurrence according to the cardiovascular risk.

In addition, it is intended to provide a cardiovascular risk assessment service that can provide various services related to cardiovascular risk to customers through health management services in an easy and secure manner.

A method of providing a cardiovascular risk assessment service according to an embodiment of the present disclosure includes the steps of registering examination data from a customer terminal through a health management service, and extracting the examination data according to risk factor items based on a preset risk quantification model. A step of quantifying the target risk for each risk factor item for each cardiovascular data among a plurality of cardiovascular data, and deriving target information for each risk factor item using the target risk and standard target table for each risk factor item. , a step of predicting information on the age of cardiovascular occurrence based on an approximation between the target absolute risk calculated according to the target risk for each risk factor item and the average absolute risk determined according to the customer information, and the target risk for each risk factor item, It may include providing health management information so that the target information for each risk factor item and the age information for cardiovascular and cerebrovascular events can be confirmed on the customer terminal through the health management service.

According to one embodiment, the risk factor items include at least one of body mass index, waist circumference, smoking status, blood pressure, taking blood pressure medication, physical activity, fasting blood sugar, taking diabetes medication, total cholesterol, GFR, dipstick proteinuria, and alcohol consumption. Includes more.

According to one embodiment, the step of registering includes checking whether risk factor items are missing from the examination data through data validation, and based on whether or not the risk factor items are missing, customers are divided from a preset questionnaire template. It may include creating a customized questionnaire template and updating the response information received by providing the customized questionnaire template to the customer terminal through a health care service by merging it with the examination data.

According to one embodiment, the step of quantifying is by comparing and analyzing the target risk for each risk factor item and the evaluation standard table, so that the target risk for each risk factor item is classified into one of a safety level, a caution level, and a risk level. It includes the step of identifying by evaluation grade, and the evaluation standard table may be a table listing numerical values or condition information for each evaluation grade by risk factor item.

According to one embodiment, the step of quantifying is a step of calculating a composite relative risk using the target risk and standard constant for each of the quantified risk factor items, and calculating the composite relative risk according to personal information from a preset relative risk table. A step of calculating an adjusted composite relative risk by dividing by the determined average composite relative risk, and a step of calculating the target absolute risk by multiplying the adjusted composite relative risk by the average absolute risk determined according to personal information from a preset average absolute risk table. It can be included.

According to one embodiment, the health management information includes assessment date, cardiovascular age, probability of occurrence of cardiovascular disease, target risk and goal information for each risk factor item, cardiovascular age predicted for improvement, probability of occurrence of cardiovascular disease, and video coaching. It includes a service interlocking link, and the step of providing the health management information includes providing a video coaching service for improving lifestyle habits between the customer terminal and the health manager terminal to the customer terminal through the health management information. can do.

According to one embodiment, the providing step includes collecting recruitment group screening information, and based on whether or not the risk is improved as confirmed from the recruitment group screening information, feedback is received as a preventive management method is requested through the health management service from each recruitment group terminal. A step of receiving input, receiving feedback on the preventive management method, selectively labeling the recruitment group examination information with the corresponding preventive management method, through machine learning using the recruitment group examination information as input and the preventive management method as output. Learning a deep learning-based preventive management method derivation model, applying the target risk for each risk factor item and age and gender information confirmed from the examination data to the preventive management method derivation model to derive a customized preventive management method. It may include providing a preventive management method tailored to the customer in response to an alternative preventive management method queried through the health care service from the customer terminal.

According to one embodiment, the step of providing the customer-tailored preventive care method includes searching for preventive care lecture content for body improvement through a video sharing platform using characteristic keywords extracted from the customer-tailored preventive care method and linking the corresponding link. It may include the step of sharing to the customer terminal.

A computer-readable storage medium storing at least one program according to an embodiment, wherein the at least one program may include instructions for performing at least one of the above-described methods.

An apparatus for providing a cardiovascular risk assessment service according to an embodiment includes a computer-readable storage medium storing at least one or more processors and at least one program configured to be executed by the at least one or more processors, wherein the at least one program is It may include instructions for performing at least one of the above-described methods.

According to embodiments of the present disclosure, a method and apparatus for providing a cardiovascular risk assessment service can increase awareness of preventive management for cardiovascular diseases by predicting information on the age of occurrence of cardiovascular diseases according to the cardiovascular risk and providing services to customers.

In addition, by providing various services related to cardiovascular risk to customers through health management services in an easy and secure form, we support them to more easily identify the risk of cardiovascular disease and prevent the loss of health-related information. It can be minimized.

Meanwhile, the effects according to the embodiments are not limited to those mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below.

1 is an exemplary diagram of a system according to one embodiment.
Figure 2 is an exemplary diagram of health management information according to an embodiment.
Figure 3 is an exemplary diagram of a result report according to one embodiment.
Figure 4 is a block diagram of a risk analysis unit according to an embodiment.
Figure 5 is an exemplary diagram of a relative risk table according to one embodiment.
Figure 6 is a block diagram of an integrated service unit according to an embodiment.
Figure 7 is a flowchart showing the operation of a cardiovascular risk assessment service providing device according to an embodiment.
Figure 8 is a flowchart showing the operation of a data register according to an embodiment.
Figure 9 is a flowchart showing the operation of the risk analysis unit according to one embodiment.
Figure 10 is a flow chart showing the operation of the integrated service unit according to one embodiment.

Hereinafter, embodiments will be described in detail with reference to the attached drawings. However, various changes can be made to the embodiments, so the scope of the patent application is not limited or limited by these embodiments. It should be understood that all changes, equivalents, or substitutes for the embodiments are included in the scope of rights.

Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be modified and implemented in various forms. Accordingly, the embodiments are not limited to the specific disclosed form, and the scope of the present specification may include changes, equivalents, or substitutions included in the technical spirit.

Terms such as first or second may be used to describe various components, but these terms should be interpreted only for the purpose of distinguishing one component from another component. For example, a first component may be named a second component, and similarly, the second component may also be named a first component.

When a component is referred to as being “connected” to another component, it should be understood that it may be directly connected or connected to the other component, but that other components may exist in between.

The terms used in the examples are for descriptive purposes only and should not be construed as limiting. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that this does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

Spatially relative terms such as “below”, “beneath”, “lower”, “above”, “upper”, etc. are used as a single term as shown in the drawing. It can be used to easily describe the correlation between a component and other components. Spatially relative terms should be understood as terms that include different directions of components during use or operation in addition to the directions shown in the drawings. For example, if you flip a component shown in a drawing, a component described as "below" or "beneath" another component will be placed "above" the other component. You can. Accordingly, the illustrative term “down” may include both downward and upward directions. Components can also be oriented in other directions, so spatially relative terms can be interpreted according to orientation.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by a person of ordinary skill in the technical field to which the embodiments belong. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and unless explicitly defined in the present application, should not be interpreted in an ideal or excessively formal sense. No.

In addition, when describing with reference to the accompanying drawings, identical components will be assigned the same reference numerals regardless of the reference numerals, and overlapping descriptions thereof will be omitted. In describing the embodiments, if it is determined that detailed descriptions of related known technologies may unnecessarily obscure the gist of the embodiments, the detailed descriptions are omitted.

A cardiovascular risk assessment service providing system 2000 according to an embodiment is described with reference to FIGS. 1 to 3 .

FIG. 1 is an exemplary diagram of a system according to an embodiment, FIG. 2 is an exemplary diagram of health management information according to an embodiment, and FIG. 3 is an exemplary diagram of a result report according to an embodiment.

Result Report When described with reference to Figure 1, the cardiovascular risk assessment service provision system 2000 may include a customer terminal 10 and a cardiovascular risk assessment service provision device 1000.

The cardiovascular risk assessment service providing device 1000 according to the embodiment corresponds to a server for providing a cardiovascular risk assessment service to the customer terminal 10, and the server is connected to a memory storing a program or software module and the memory. may include a processor that executes a program.

Specifically, the processor may be configured to include a data registration unit 100, a data classification unit 200, a risk analysis unit 300, and an integrated service unit 400, and some of the above components may not necessarily be included. , depending on the implementation, some or all of them may be selectively included, and some additional components not shown may also be included.

First, the data register 100 can register examination data from the customer terminal 10 through the health management service, classify it by customer, and store it in the storage DB 500.

The health care service according to one embodiment is a program or application that receives examination data or preventive management methods from the customer terminal 10 and provides various services related to the cardiovascular system, and is provided through a web server (not shown) to each customer terminal (e.g., 10_1~10_N) and can be installed.

At this time, the checkup data may refer to the customer's health information confirmed through a health checkup or blood test.

Next, the data classification unit 200 may classify a plurality of cardiovascular data extracted from the examination data according to risk factor items, identify each customer, and register them in the storage DB 500.

Risk factor items according to one embodiment include at least one of body mass index, waist circumference, smoking status, blood pressure, taking blood pressure medication, physical activity, fasting blood sugar, taking diabetes medication, total cholesterol, GFR, dipstick proteinuria, and amount of alcohol consumed. It can be included.

Next, the risk analysis unit 300 determines the target risk for each risk factor item for each cardiovascular data among the plurality of cardiovascular data extracted according to the risk factor items from the examination data, based on the preset risk quantification model. It can be quantified.

The preset risk quantification model according to one embodiment may be a table that includes at least one of status level, gender-based risk, remarks, variables, and survey item contents for each risk factor item.

For example, when the risk factor item is physical activity, the condition level is divided into 3 or more times a week and 2 or more times a week, and the standard risk for men is 1 for 3 or more times a week and 1.2 for 2 or more times a week. Remarks is blank, the variable is the sum of the number of times per week of high-intensity exercise and moderate-intensity exercise, and the survey items may include physical activity evaluation items 6 and 7.

For example, among the plurality of cardiovascular and cerebrovascular data, the body mass index is 25.5, and in the case of a male, the target risk for body mass index may be 1.04.

According to the embodiment, the risk analysis unit 300 compares and analyzes the target risk for each quantified risk factor item and the evaluation standard table to evaluate the target risk for each risk factor item as one of safety level, caution level, and risk level. It can be identified by grade.

In other words, the risk analysis unit 300 identifies and displays the target risk for each risk factor item in each color corresponding to each evaluation grade, so that the preventive management service unit 450 below is used to visually express the customer's health status. We can support the provision of health traffic light graphics.

The evaluation standard table according to one embodiment may include a first table that identifies the waist circumference risk for each abdominal body type according to the BMI index and a second table that lists numerical values or condition information for each risk factor item for each evaluation grade. .

Specifically, in the first table, the BMI index is classified into less than 18.5, 18.5 or more to less than 23.0, 23.0 or more to less than 25.0, 25.0 or more to less than 30.0, and 30.0 or more, and abdominal body type is classified as normal and obese, Each intersection point between BMI index and abdominal body type can include an identified waist circumference risk.

For example, if the BMI index is less than 18.5 and the abdominal body shape is normal, the waist circumference risk is identified as a caution grade. If the BMI index is in the range of 18.5 to 23.0 and the abdominal body shape is normal, the waist circumference risk is identified as a safe grade. If the BMI index is in the range of 25.5 to 30.0 and the abdominal body type is obese, the waist circumference risk can be identified as a risk level.

In addition, the second table classifies the risk factor items as blood pressure, fasting blood sugar, total cholesterol, drinking, smoking, and physical activity, and also classifies them as safety level, caution level, and risk level, so that the intersection between risk factor items and evaluation level is classified into safety level, caution level, and risk level. Each point can contain identified numerical values or condition information.

Specifically, blood pressure is classified into taking blood pressure medication and not taking blood pressure medication, fasting blood sugar is categorized into taking diabetes medication and not taking diabetes medication, and total cholesterol is classified into taking dyslipidemia medication and taking dyslipidemia medication according to below a certain level. It is classified into non-taking, taking dyslipidemia medication above a certain level, and not taking dyslipidemia medication, and drinking can be classified according to gender and age.

For example, if the patient is not taking diabetes medication and the fasting blood sugar level is 80 among the target risks for each quantified risk factor item, the risk analysis unit 300 can identify the target risk for fasting blood sugar as a safety grade. In addition, if the patient is not taking diabetes medication and the fasting blood sugar level is 110 among the target risks for each quantified risk factor item, the risk analysis unit 300 can identify the target risk for fasting blood sugar as a caution level. In addition, if the patient is not taking diabetes medication and the fasting blood sugar level is 135 among the target risks for each quantified risk factor item, the risk analysis unit 300 can identify the target risk for fasting blood sugar as a risk grade.

In this way, the risk analysis unit 300 can identify each target risk for each risk factor item as one of the safety level, caution level, and risk level.

Next, the integrated service department 400 can derive target information for each risk factor item using the target risk and standard target table for each risk factor item.

The target information for each risk factor item according to an embodiment may be a value changed from the target risk value for each risk factor item according to a standard target table.

At this time, the standard target table may be a table listing target information for each risk factor item.

Specifically, the target information for the obesity assessment item includes the calculated weight value corresponding to BMI 23, the condition of waist circumference less than 90cm for men, and the condition less than 85cm for women, and the goal information for the physical activity item is the condition of 5 or more times a week, and the blood pressure item. The target information for the fasting blood sugar item includes the condition of less than 100 mg/dL, and the target information for the cholesterol item includes the condition of total cholesterol less than 200 mg/dL and LDL cholesterol less than 130 mg/dL, The goal information for the smoking item includes non-smoking, maintaining smoking cessation, and quitting smoking according to smoking status, and the goal information for the drinking item is 2 drinks per day for men under 65 years of age, 1 drink per day for men over 65 years of age, and 1 drink per day for women. It can be included.

For example, if the smoking item is confirmed to be a current smoking state based on the target risk for each risk factor item, the integrated service department 400 may use the standard goal table to derive goal information for the smoking item to quit smoking.

The integrated service department 400 according to an embodiment of the present disclosure can predict information on the age of cardiovascular occurrence based on an approximation between the target absolute risk calculated according to the target risk for each risk factor item and the average absolute risk determined according to customer information. You can.

Specifically, the integrated service department 400 calculates an approximate value by age between the target absolute risk and the average absolute risk using any one of the first and second average absolute risk tables corresponding to customer information, and sets the minimum value among the approximate values by age. The corresponding age information can be output as cardiovascular onset age information.

The average absolute risk table according to one embodiment is a table listing the average absolute risk by gender and age, and may include a first and second average absolute risk table.

Specifically, the first average absolute risk is a table in which the average absolute risk of men is quantified by age. For a 20-year-old man, the average absolute risk is 99, for a 21-year-old man, the average absolute risk is 138, and for a 66-year-old man, the average absolute risk is 99. In this case, the average absolute risk could be 13.733. In addition, the second average absolute risk is a table in which the average absolute risk of women is quantified by age. For a 20-year-old woman, the average absolute risk may be 92, and for a 66-year-old woman, it may be 10.248.

For example, if the customer information corresponds to a male, the integrated service department 400 uses the target absolute risk and the first average absolute risk table to determine approximate values by age, for example, 11 for 20 years old, 28 for 21 years old, For a 22-year-old, you can calculate 68, etc. At this time, the integrated service unit 400 may output age information corresponding to the minimum value, for example, 11 among the approximate values for each age, for example, 20 years old, as information on the age of cardiovascular occurrence.

In addition, the integrated service department 400 can provide health management information so that the target risk for each risk factor item, target information for each risk factor item, and information on the age of cardiovascular occurrence can be checked on the customer terminal 10 through the health management service. there is.

As shown in FIG. 2, health management information according to an embodiment includes assessment date, cardiovascular age, probability of occurrence of cardiovascular disease, target risk and goal information for each risk factor item, cardiovascular age predicted at the time of improvement, and cardiovascular disease. It may include disease occurrence probability and links to video coaching services.

This cardiovascular risk assessment service providing device 1000 performs each operation of the data register 100, data classification unit 200, risk analysis unit 300, and integrated service unit 400 by at least one processor. You can.

According to one embodiment, the integrated service unit 400 provides health management information by providing a video coaching service to improve lifestyle habits between the customer terminal 10 and the health manager terminal 20, based on the age information of cardiovascular and cerebrovascular events. It can be selectively provided to the customer terminal 10 through.

Specifically, if the age confirmed from personal information is lower than the information on the age of cardiovascular occurrence, the integrated service department 400 selectively provides the video coaching service to the customer terminal 10 through health management information, thereby providing the video coaching service. effectiveness can be increased.

According to another embodiment, the integrated service department 400 provides at least one customer-customized method among a plurality of preventive management methods based on the numerical difference value for each risk factor item between the target risk for each risk factor item and the target information for each risk factor item. You can choose preventive management methods.

A plurality of preventive management methods according to one embodiment may include regular physical activity such as jogging or cycling, maintaining a diet, smoking cessation, abstinence from alcohol, regular health checkups, treatment suggestions, etc.

For example, if the numerical difference value for each risk factor item is within a certain range, the integrated service department 400 may select regular physical activity among a plurality of preventive management methods as a customized preventive management method for the customer. In addition, if the numerical difference value for each risk factor item exceeds a certain range, the integrated service department (400) selects regular physical activity, maintaining a diet, smoking cessation, abstinence from drinking, regular health checkups, and treatment suggestions as customized preventive management methods. It may be possible.

According to another embodiment, the integrated service unit 400 reflects customer information confirmed from examination data, information on the age of cardiovascular occurrence, and at least one customer-customized preventive management method according to a health care report template to create a result report. .

Then, the integrated service unit 400 receives the examination data from the customer terminal 10 through the health management service and uses the public key corresponding to the secret key given to the customer terminal 10 to provide a result report. It can be encrypted and provided to the customer terminal 10 through a health care service.

As shown in FIG. 3 , the result report according to one embodiment may include a editable writing area and a non-editable form area according to customer information, information on the age of cardiovascular and cerebrovascular events, and at least one customized preventive management method for the customer.

According to another embodiment, the integrated service unit 400 provides first heart rate information and checkup measured through a radar sensor (not shown) provided in the customer terminal 10 when the information on the age of cardiovascular occurrence is lower than the actual age. Based on whether there is a difference between the second heart rate information extracted from the data, it is possible to verify whether the examination data is falsified.

That is, the integrated service unit 400 controls the customer terminal 10 to measure the first heart rate information through a radar sensor (not shown) provided in the customer terminal 10 in order to verify whether the examination data is falsified. can do.

Here, the radar sensor (not shown) may refer to a sensor that detects breathing or heart rate by analyzing the frequency, reflection period, and signal strength of the UWB radar electromagnetic waves reflected as UWB radar electromagnetic waves are transmitted in one direction. .

According to another embodiment, the integrated service unit 400, when the information on the age of cardiovascular occurrence is lower than the actual age, the body shape extracted from the 3D body image captured through a camera (not shown) provided in the customer terminal 10 The first body weight and height length can be estimated based on the volume.

At this time, the integrated service unit 400 can verify whether the examination data is falsified based on whether the difference between the first weight and height length and the second weight and height length extracted from the examination data is within a certain range.

For example, if the information on the age of cardiovascular occurrence is lower than the actual age, the integrated service unit 400 provides the customer terminal 10 with a 3D shooting guide for obtaining a 3D body image, thereby providing a plurality of body images to be captured. You can receive it. At this time, the integrated service unit 400 may output a 3D body image by combining a plurality of body images using a preset synthesis program. Then, the integrated service unit 400 can estimate the first weight and height through body shape object analysis of the 3D body shape image.

Figure 4 is a block diagram of a risk analysis unit according to an embodiment, and Figure 5 is an exemplary diagram of a relative risk table according to an embodiment.

When described with reference to FIG. 4 , the risk analysis unit 300 of FIG. 1 may include first to third calculation units 310 to 330.

First, the first calculation unit 310 can calculate a composite relative risk using the target risk and standard constant for each quantified risk factor item.

The composite relative risk according to one embodiment may mean the sum of the standard constant and the sum of the difference obtained by removing the standard constant for each risk factor item from the target risk for each quantified risk factor item.

Here, the reference constant may be 1.

For example, assuming that the target risk for each quantified risk factor item is 1.15, 1.44, 1.60, 1.25, and 1.22, the difference after removing the standard constant for each risk factor item is 0.15, 0.44, 0.60, 0.25, and 0.22, and the summed value is 1.66, and the composite relative risk can be 2.66.

Depending on the embodiment, the first calculation unit 310 may calculate the correction composite relative risk based on the correction target risk for each risk factor item corrected according to the possibility and range of correction for the target risk for each risk factor item.

The possibility and range of correction according to one embodiment is that for the obesity item, the risk subject to correction is 1.00, for the smoking item, the risk subject to correction is 1.30 for men and 1.20 for women, and for the blood pressure item, the risk subject to correction is 1.00, and the amount of physical activity In the case of , the risk subject to correction is 1.00, in the case of blood sugar items, the risk subject to correction is 1.00, in the case of total cholesterol items, the risk subject to correction is 1.00, and in the case of kidney function items, the risk subject to correction may be an impossible variable. At this time, in the case of those taking blood sugar and blood pressure, the risk to be corrected may be a variable that cannot be corrected.

Next, the second calculation unit 320 may calculate the adjusted composite relative risk by dividing the composite relative risk by the average composite relative risk determined according to personal information from a preset relative risk table.

As shown in FIG. 5, the preset relative risk table according to one embodiment may be a table listing the average composite relative risk preset according to age and gender.

At this time, the personal information may include the customer's age and gender information confirmed from the examination data.

Specifically, the second calculation unit 320 may register in advance the average composite relative risk table in the storage DB 500 that lists the composite relative risks of the previously collected recruitment group by classifying them by gender and age.

At this time, when the composite relative risk is calculated, the second calculation unit 320 may extract the average composite relative risk corresponding to the personal information from the average composite relative risk table and determine it as the calculation target for the adjusted composite relative risk.

Next, the third calculation unit 330 may calculate the target absolute risk by multiplying the adjusted composite relative risk by the average absolute risk determined according to personal information from a preset average absolute risk table.

Specifically, the third calculation unit 330 registers the first and second average absolute risk tables, which are listed by classifying the already collected absolute risks of the recruitment group according to gender and age, in the storage DB 500 in advance. You can.

At this time, when the adjusted composite relative risk is calculated, the third calculation unit 330 extracts the average absolute risk corresponding to the personal information from the first and second average absolute risk tables and determines the calculation target for the target absolute risk. You can.

Depending on the embodiment, the third calculation unit 330 may calculate the absolute risk to be calibrated based on the calibrated composite relative risk, the calibrated average composite relative risk, and the average absolute risk calculated according to the calibrated composite relative risk.

Figure 6 is a block diagram of an integrated service unit according to an embodiment.

1 and 6, the integrated service unit 400 includes an information collection unit 410, a request input unit 420, a labeling unit 430, a learning unit 440, and a preventive management service unit 450. may include.

First, the information collection unit 410 may collect recruitment group screening information in advance and store it in the storage DB 500.

Recruitment group screening information according to one embodiment may include target risk history and age and gender information for each risk factor item of each recruitment target.

According to the embodiment, the information collection unit 410 transmits a request message requesting consent to participate in the recruitment group to the customer terminal 10 through the health management service, and based on the approval signal received as feedback, the customer information and risk factors The target risk for each item can be updated in the population screening information.

Next, the request input unit 420 can receive feedback from each recruitment group terminal (30_1 to 30_N) by requesting a preventive management method through the health management service, based on whether the risk has improved as confirmed from the recruitment group examination information.

Next, as the labeling unit 430 receives feedback on the preventive management method, it can selectively label the corresponding preventive management method in the recruitment group screening information.

Next, the learning unit 440 can learn a deep learning-based preventive management method derivation model through machine learning that uses recruitment group screening information as input and preventive management method as output.

According to one embodiment, the deep learning-based customized preventive management method derivation model is an artificial neural network (ANN) that receives the target risk for each risk factor item quantified through the risk analysis unit 300 and outputs a customized preventive management method. ) can be.

Next, the preventive management service department 450 applies the target risk for each risk factor item quantified through the risk analysis department 300 and the age and gender information confirmed from the examination data to the preventive management method derivation model, Preventative management methods can be derived.

At this time, the preventive care service unit 450 may respond to alternative preventive care methods queried through the health care service from the customer terminal 10 and provide a customized preventive care method based on artificial intelligence.

According to one embodiment, the preventive management service department 450 uses characteristic keywords extracted from customer-customized preventive management methods to provide preventive management that has a certain number of views or more among preventive management lecture contents for body improvement through a video sharing platform. You can search for lecture content and share the link to the customer terminal 10.

For example, if the feature keyword extracted from the customer-customized preventive management method is jogging, the preventive management service unit 450 can search for jogging lecture contents through a search on a video sharing platform about jogging. At this time, the preventive management service unit 450 may select preventive management lecture contents that have a certain number of views or more among the jogging lecture contents and share the web address link with the customer terminal 10.

According to another embodiment, the preventive care service unit 450 may selectively display health-related advertising content in the health care information based on the number of visits confirmed through the health care service from the customer terminal 10.

For example, if the number of visits is more than a certain number, the preventive care service department 450 may determine that the customer is highly interested in health care. At this time, the preventive care service unit 450 can increase advertising efficiency by displaying health-related advertising content on health care information provided to customers who are highly interested in health care.

According to another embodiment, the preventive management service unit 450 generates a health traffic light graphic based on each evaluation grade for the target risk for each risk factor item and serves it to the customer terminal 10 through a health management service, It can help customers more easily determine their health status without having to figure out the risk level according to the target risk level for each risk factor item.

Here, the health traffic light graphic may be a graphic in which the target risk for each risk factor item is identified and displayed in a preset color according to each evaluation grade. For example, the health traffic light graphic may be colored red if the evaluation level is a safety level, yellow if the evaluation level is a caution level, and green if the evaluation level is a safety level.

According to another embodiment, the preventive care service unit 450 chats for exchanging opinions between a plurality of customers through a health care service based on whether or not the customer has authenticated the customer information transmitted from the customer terminal 10. By granting access rights to the service to the customer terminal 10, the possibility of opinions among customers being leaked to the outside can be minimized.

Figure 7 is a flowchart showing the operation of a cardiovascular risk assessment service providing device according to an embodiment.

Referring to FIGS. 1 and 7 , first, in step S110, the data register 100 may register examination data from the customer terminal 10 through the health management service.

Then, in step S120, the risk analysis unit 300 determines the risk factor items for each cardiovascular data among the plurality of cardiovascular data extracted according to the risk factor items from the examination data based on the preset risk quantification model. The risk of each target can be quantified.

Depending on the embodiment, in step S120, the risk analysis unit 300 compares and analyzes the target risk for each quantified risk factor item and the evaluation standard table, and determines the target risk for each risk factor item among the safety level, caution level, and risk level. It can be identified by any one evaluation level.

Then, in step S130, the integrated service department 400 can derive target information for each risk factor item using the target risk and standard target table for each quantified risk factor item.

At this time, in step S140, the integrated service department 400 can predict information on the age of cardiovascular occurrence based on the approximate value between the target absolute risk calculated according to the target risk for each risk factor item and the average absolute risk determined according to customer information. there is.

Thereafter, in step S150, the integrated service department 400 provides health management information so that the target risk for each risk factor item, target information for each risk factor item, and information on the age of cardiovascular occurrence can be checked on the customer terminal 10 through the health management service. can be provided.

According to the embodiment, in step S150, the integrated service unit 400 provides a video coaching service for improving lifestyle habits between the customer terminal 10 and the health manager terminal 20 to the customer terminal 10 through health management information. can be provided.

Figure 8 is a flowchart showing the operation of a data register according to an embodiment.

Referring to FIGS. 1 and 8 , first, in step S210, the data register 100 may check whether risk factor items are missing through a data validity check from the examination data.

At this time, in step S220, the data register 100 may generate a customer-customized questionnaire template selected from preset questionnaire templates based on whether risk factor items are omitted.

Then, in step S230, the data register 100 may provide the customer-customized questionnaire template to the customer terminal 10 through the health management service and update the received response information by further merging it with the examination data.

Figure 9 is a flowchart showing the operation of the risk analysis unit according to one embodiment.

Referring to FIGS. 4 and 9 , first, in step S310, the first calculation unit 310 may calculate a composite relative risk using the target risk and standard constant for each quantified risk factor item.

Then, in step S320, the second calculation unit 320 may calculate the adjusted composite relative risk by dividing the composite relative risk by the average composite relative risk determined according to personal information from a preset relative risk table.

Then, in step S330, the third calculation unit 330 may calculate the target absolute risk by multiplying the adjusted composite relative risk by the average absolute risk determined according to personal information from a preset average absolute risk table.

Figure 10 is a flow chart showing the operation of the integrated service unit according to one embodiment.

6 and 10 , first, in step S410, the information collection unit 410 may collect recruitment group examination information in advance and store it in the storage DB 500.

Then, in step S420, the request input unit 420 can receive feedback from each recruitment group terminal (30_1 to 30_N) by requesting a preventive management method through the health management service, based on whether the risk has improved as confirmed from the recruitment group examination information. there is.

Then, in step S430, the labeling unit 430 may selectively label the corresponding preventive management method in the population screening information as the preventive management method is received as feedback.

At this time, in step S440, the learning unit 440 can learn a deep learning-based preventive management method derivation model through machine learning that uses the recruitment group screening information as input and the preventive management method as output.

Then, in step S450, the preventive management service department 450 uses the target risk for each risk factor item quantified through the risk analysis department 300 and personal information confirmed from the examination data, such as age and gender information, into a preventive management method derivation model. By applying it, a customized preventive management method can be derived.

According to the embodiment, in step S450, the preventive care service unit 450 searches for preventive care lecture content for body improvement through a video sharing platform using characteristic keywords extracted from the customer-customized preventive care method and clicks on the corresponding link. It can be shared with the customer terminal (10).

The embodiments described above may be implemented with hardware components, software components, or a combination of hardware components and software components. For example, the devices, methods, and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, and a field programmable gate (FPGA). It may be implemented using one or more general-purpose or special-purpose computers, such as an array, programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. A processing device may perform an operating system (OS) and one or more software applications that run on the operating system. Additionally, a processing device may access, store, manipulate, process, and generate data in response to the execution of software. For ease of understanding, a single processing device may be described as being used, but those skilled in the art will understand that the processing device includes multiple processing elements or multiple types of processing elements. You can see that it can be done. For example, a processing device may include a plurality of processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are possible.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. Computer-readable media may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the medium may be specially designed and configured for the embodiment or may be known and usable by those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -Includes optical media (magneto-optical media) and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. A hardware device may be configured to operate as one or more software modules to perform the operations of an embodiment, and vice versa.

Software may include a computer program, code, instructions, or a combination of one or more of these, which may configure a processing unit to operate as desired, or may be processed independently or collectively. You can command the device. Software or data means any type of machine, component, physical device, virtual equipment, computer storage medium or device to be interpreted by or to provide instructions or data to a processing device, or It can be permanently or temporarily embodied in a transmitted signal wave. Software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

As described above, although the embodiments have been described with limited drawings, those skilled in the art can apply various technical modifications and variations based on this. For example, the described techniques are performed in a different order than the described method, or components of the described system, structure, device, circuit, etc. are combined or combined in a form different from the described method, or other components or equivalents are used. Adequate results can be achieved even if replaced or substituted by water.

Therefore, other implementations, other embodiments, and equivalents of the claims also fall within the scope of the following claims.

Claims (12)

A method of providing a cardiovascular risk assessment service performed by at least one processor, comprising:
A step of registering examination data from a customer terminal through a health management service;
Based on a preset risk quantification model, quantifying the target risk for each risk factor item for each cardiovascular data among a plurality of cardiovascular data extracted according to risk factor items from the examination data;
Deriving target information for each risk factor item using the target risk and standard target table for each risk factor item;
Predicting information on the age of cardiovascular occurrence based on an approximation between the target absolute risk calculated according to the target risk for each risk factor item and the average absolute risk determined according to the customer information; and
Providing health management information so that the target risk for each risk factor item, target information for each risk factor item, and the age information for cardiovascular and cerebrovascular events can be confirmed on the customer terminal through the health management service.
Including,
The step of quantifying the target risk is,
Calculating a composite relative risk using the target risk and standard constant for each quantified risk factor item;
Calculating an adjusted composite relative risk by dividing the composite relative risk by an average composite relative risk determined according to personal information from a preset relative risk table; and
A method of providing a cardiovascular risk assessment service comprising calculating the target absolute risk by multiplying the adjusted composite relative risk by an average absolute risk determined according to personal information from a preset average absolute risk table.


According to paragraph 1,
The risk factors include at least one of body mass index, waist circumference, smoking status, blood pressure, taking blood pressure medication, physical activity, fasting blood sugar, taking diabetes medication, total cholesterol, GFR, dipstick proteinuria, and alcohol consumption. How to provide vascular risk assessment services.
According to paragraph 1,
The step of registering the examination data is,
Checking whether risk factor items are missing from the examination data through data validation;
Creating a customer-customized questionnaire template divided from a preset questionnaire template based on whether or not the risk factor items are omitted; and
A step of updating the response information received by providing the customer-customized questionnaire template to the customer terminal through a health management service by merging it with the examination data.
Method for providing cardiovascular risk assessment services, including.
According to paragraph 1,
The step of quantifying the target risk is,
Comparing and analyzing the quantified target risk for each risk factor item and the evaluation standard table, identifying the target risk for each risk factor item as any one of the safety level, caution level, and risk level.
Including,
The evaluation standard table is a table in which numerical values or condition information for each evaluation grade are listed by risk factor item,
How to provide cardiovascular risk assessment services.
delete According to paragraph 1,
The health management information includes assessment date, cardiovascular age, probability of occurrence of cardiovascular disease, target risk and goal information for each risk factor, predicted cardiovascular age upon improvement, probability of occurrence of cardiovascular disease, and link to video coaching service. ,
The step of providing the health care information is,
Providing a video coaching service for improving lifestyle habits between the customer terminal and the health manager terminal to the customer terminal through the health management information.
Method for providing cardiovascular risk assessment services, including.
According to paragraph 1,
The step of providing the health care information is,
Collecting recruitment group screening information;
Receiving feedback from each recruitment group terminal in response to a request for a preventive management method through the health management service, based on whether the risk is improved as confirmed from the recruitment group examination information;
In response to receiving feedback on the preventive management method, selectively labeling the population screening information with the corresponding preventive management method;
Learning a deep learning-based preventive management method derivation model through machine learning using the recruitment group screening information as input and the preventive management method as output;
Deriving a preventive management method tailored to the customer by applying the target risk for each risk factor item and age and gender information confirmed from the examination data to the preventive management method derivation model; and
Providing a preventive management method tailored to the customer in response to an alternative preventive management method queried through the health care service from the customer terminal.
Method for providing cardiovascular risk assessment services, including.
In clause 7,
The step of providing the customer-tailored preventive management method is,
Using characteristic keywords extracted from the customer-customized preventive care method, searching for preventive care lecture content for body improvement through a video sharing platform and sharing the corresponding link to the customer terminal.
Method for providing cardiovascular risk assessment services, including.
According to paragraph 1,
The step of calculating the adjusted composite relative risk is,
Pre-registering an average composite relative risk table that lists the composite relative risks of the already collected recruitment group by classifying them by gender and age; and
When the composite relative risk is calculated, extracting the average composite relative risk corresponding to the personal information from the average composite relative risk table and determining it as a calculation target for the adjusted composite relative risk.
Method for providing cardiovascular risk assessment services, including.
According to paragraph 1,
The step of calculating the adjusted composite relative risk is,
Pre-registering first and second average absolute risk tables that list the absolute risks of the previously collected recruitment group by classifying them by gender and age; and
When the adjusted composite relative risk is calculated, extracting the average absolute risk corresponding to the personal information from the first and second average absolute risk tables and determining it as a calculation target for the target absolute risk.
Method for providing cardiovascular risk assessment services, including.
A computer-readable storage medium storing at least one program,
The at least one program includes instructions for performing the method of providing the cardiovascular risk assessment service of any one of claims 1 to 4 and 6 to 10.
Computer readable storage medium.
As a device,
at least one processor; and
A computer-readable storage medium storing at least one program configured to be executed by the at least one processor,
The at least one program includes instructions for performing the method of providing the cardiovascular risk assessment service of any one of claims 1 to 4 and 6 to 10.
Device.

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