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WO2014175542A1 - Appareil et méthode de prévision de bio-âge - Google Patents

Appareil et méthode de prévision de bio-âge Download PDF

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Publication number
WO2014175542A1
WO2014175542A1 PCT/KR2014/001236 KR2014001236W WO2014175542A1 WO 2014175542 A1 WO2014175542 A1 WO 2014175542A1 KR 2014001236 W KR2014001236 W KR 2014001236W WO 2014175542 A1 WO2014175542 A1 WO 2014175542A1
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Prior art keywords
value
examination
age
item
screening
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Ceased
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PCT/KR2014/001236
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English (en)
Korean (ko)
Inventor
유진호
김양석
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BIO AGE CO LTD
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BIO AGE CO LTD
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Priority to JP2016507876A priority Critical patent/JP6219498B2/ja
Priority to CN201480022739.0A priority patent/CN105144174B/zh
Publication of WO2014175542A1 publication Critical patent/WO2014175542A1/fr
Anticipated expiration legal-status Critical
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • the present invention relates to a body age prediction apparatus and method. More specifically, the screening values for each screening item of this period (t) are input, and the screening values for each screening item of the next period (t + 1) are predicted through statistical data for each screening item. An apparatus and method for performing the same, and also an apparatus and method for predicting the living body age of the next period (t + 1) using the predicted respective examination values.
  • Korean Patent Laid-Open No. 2007-0080852 discloses a device and method for measuring the age of the living body by receiving various examination values.
  • the technical problem to be solved by the present invention is to provide an apparatus for predicting the future examination value of the examinee who provided the current examination value for a specific examination item using a plurality of accumulated statistical data.
  • Another technical problem to be solved by the present invention is to provide a method for predicting future examination values of a subject who provides a current examination value for a specific examination item using a plurality of accumulated statistical data.
  • Another technical problem to be solved by the present invention is to generate an interpolation function for modeling parameters through extrapolation using a plurality of accumulated statistical data, and to provide future check values of the examinee who provided the current check values. It is to provide an apparatus for predicting using the interpolation function.
  • Another technical problem to be solved by the present invention is to generate an interpolation function for modeling parameters through extrapolation using a plurality of accumulated statistical data, and to provide future check values of the examinee who provided the current check values. It is to provide a method for predicting using the interpolation function.
  • Another technical problem to be solved by the present invention is to generate an interpolation function that models a parameter through extrapolation using a plurality of accumulated statistical data, and to use the statistical data and the results predicted using the interpolation function. It is to provide a device that accurately reflects all the predicted results and predicts the future examination values of the examinees who have provided the current examination values with high accuracy.
  • Another technical problem to be solved by the present invention is to generate an interpolation function that models a parameter through extrapolation using a plurality of accumulated statistical data, and to use the statistical data and the results predicted using the interpolation function. By reflecting all the predicted results, the present invention provides a method for accurately predicting future examination values of the examinees who provided the current examination values.
  • Another technical problem to be solved by the present invention is for each of a plurality of check-up items, predict the check-up value of the next cycle using the check-up value of this cycle, and predict the living age of the next cycle using the predicted check-up value It is to provide a device to.
  • Another technical problem to be solved by the present invention is for each of a plurality of check-up items, predict the check-up value of the next cycle using the check-up value of this cycle, and predict the living age of the next cycle using the predicted check-up value To provide a way.
  • the examination numerical value predicting apparatus has a mean value AVG (T) and a standard deviation SD (T) of the first examination item for this age (T).
  • the statistical information receiver receiving the mean value AVG (T + 1) and the standard deviation SD (T + 1) of the first screening item for the next age (T + 1), the examinee for this age (T)
  • the test value input unit receives the check value X (T) of the first check item of the present invention, and reflects the weight to the difference value between X (T) and AVG (T), and adds to AVG (T + 1) to examinee.
  • the device for predicting the number of examinations reports that the difference between the examination values and the average values of the examinees at this age is maintained similarly at the next age, and the average of the examination values at this age is the average of the examination values at the next age. Calculate the expected value for the next age screening item by adding the number corresponding to the difference between and the mean value.
  • a screening value predicting device has a mean value AVG (t) of the screening values for a first screening item stored in a screening data base by age of resident registration (t). And a statistical information receiver provided with a standard deviation SD (t), a diagnostic value input part provided with a diagnosis value X (T) of the first examination item for the current age (T) of the examinee, and using a polynomial extrapolation method.
  • an average predictive model generator for generating an interpolation function f (t) for AVG (t) of the first examination item and a weight of the difference value between X (T) and f (T), and then f (T + 1) ) And a checkup numerical predictor for calculating a predicted checkup value Y (T + 1) of the first checkup item for the next age (T + 1) of the examinee.
  • an apparatus for predicting a number of examinations uses an average value of examination values according to age, and generates an interpolation function that expresses the examination values according to age as a function, and uses the average value of the next age as a base value.
  • the predicted value of the next age which is a function value obtained by inputting the next age in the interpolation function, is used as a base value.
  • the difference between the diagnosis value of the examinee and the expected value of this age according to the interpolation function value is maintained similarly at the next age. Is the same as
  • the examination numerical value predicting device has a mean value AVG (t) for each resident registration age t of the examination values for the first examination items stored in the examination numerical database.
  • a statistical information receiver provided with a standard deviation SD (t)
  • a diagnostic value input part provided with a check value X (T) of the first check item of the examinee for this age (T)
  • T check value of the first check item of the examinee for this age (T)
  • An average prediction model generator for generating an interpolation function f (t) for AVG (t), after reflecting the weighted value of the difference between X (T) and AVG (T), adding the weight to AVG (T + 1)
  • a first examination value predictor that calculates a first expected examination value Y a (T + 1) of the first examination item for the next age (T + 1) of the examinee, the difference between X (T) and f (T)
  • the first examination term for the next age (T + 1) of the examinee by adding the weight to the value and adding to f (T + 1) 2nd expected numerical value predictor Y b (T + 1) of the neck and a predicted numerical value of the first examination item Y (T +) for the next age (T + 1) of the examinee.
  • the weight is SD (T + 1) / SD (T)
  • W 2 is the determination of the interpolation function f (t) for the distribution of the entire first examination item examination value stored in the examination numerical database. It may be determined based on the coefficient R 2 value.
  • the predicted checkup values are used.
  • the living age of the next age (T + 1) can be predicted.
  • the apparatus for predicting the age of the living body according to the present exemplary embodiment may calculate the average value AVG i (t) and the standard deviation SD i (t) of the screening values for the screening item X i stored in the screening data database by the respective screening item X.
  • An average prediction model generator which generates an interpolation function f i (t) for AVG i (t) for each examination item X i , after applying weights to the difference between X i (T) and AVG i (T) Calculate the first expected examination value Y ai (T + 1) of the first examination item for each examination item X i by adding AVG (T + 1) to the next age of the examinee (T + 1)
  • the first examination numerical predicting unit reflecting the weighted value to the difference between X i (T) and f i (T), and then f Calculating, for each examination item X i , the second expected examination value Y bi (T + 1) of the first examination item for the next age (T + 1) of the examinee is added to (T + 1).
  • it may include a living body age predicting unit for calculating the living body age for the next age (T + 1) of the examinee.
  • the biological age prediction apparatus may predict each examination value of the next age (T + 1) by using a regression equation instead of an interpolation function,
  • the predicted screening values can be used to predict the living age of the next age (T + 1).
  • the apparatus for predicting the age of the living body according to the present exemplary embodiment may calculate the average value AVG i (t) and the standard deviation SD i (t) of the screening values for the screening item X i stored in the screening data database by the respective screening item X.
  • the weight is SD i (T + 1) / SD i (T), and the first examination numerical predictor multiplies the difference value between X i (T) and AVG i (T) by the weight.
  • YG (T + 1) is calculated by adding to AVG i (T + 1)
  • W 2i may be a value of the coefficient of determination (R 2 ) of the regression equation f i (t).
  • the apparatus for predicting a biological age is an average value AVG i (by age) of the resident registration age (t) of the examination values for the examination item X i stored in the examination numerical database. t) and the standard deviation SD i (t) for each examination item X i , the statistical information receiver, and the examination item Xi (T) for the current age (T) of the examinee.
  • the screening levels screening of items X i examination is stored in a database value For the distribution of the whole If the coefficient of determination (R 2) value of the interpolation function f i (t) group exceeds a given limit value, after reflecting the weight to the difference value of X i (T) and f i (T) f (T + 1 ) And calculate Y i (T + 1), and if the determination coefficient value is less than or equal to the threshold, the weight is reflected in the difference between X i (T) and AVG i (T), and then AVG (T + 1).
  • the biometric age prediction apparatus reports that the reliability of the interpolation formula for the examination value is higher than the reliability of the mean value of the examination value when the explanatory power of the regression equation is high. Then, the predicted checkup value at the next age (T + 1) may be selected as the checkup value at the next age (T + 1).
  • the biometric age prediction method is performed by the biometric age prediction apparatus, wherein the screening value Xi of the examination item Xi for the current age (T) of the examinee is determined.
  • the biological age predicting device is configured to determine a mean value AVG i (t) and standard for each resident registration age (t) of the screening value for the screening item X i stored in the screening database.
  • the biological age predicting apparatus reflects a weight to a difference value between X i (T) and AVG i (T), and then adds AVG (T + 1) to the subject's subject.
  • First estimate of the first screening item for the next age (T + 1) Calculating a screening value Y ai (T + 1) for each screening item X i , wherein the biometric age predicting device reflects the weight to a difference between X i (T) and f i (T), and then f Calculating, for each examination item X i , the second expected examination value Y bi (T + 1) of the first examination item for the next age (T + 1) of the examinee is added to (T + 1).
  • the biological age prediction method is performed by the apparatus for predicting the age of the examination item Xi of the examination item Xi for the current age (T) of the examinee.
  • Receiving T) for each screening item X i wherein the biological age predicting device is configured to determine a mean value AVG i (t) and standard for each resident registration age (t) of the screening value for the screening item X i stored in the screening database.
  • the biological age predicting apparatus reflects a weight to a difference value between X i (T) and AVG i (T), and then adds AVG (T + 1) to the subject's subject.
  • calculating for each examination item X i is the physiological age prediction unit, X i (T) and f i (T), f a second expected check-value of the examination items X i for the next year (T + 1) of the examinee by summing the (T + 1) Y bi ( T + 1) a, the method comprising: calculating, for each examination item X i
  • the apparatus for predicting the age of the living body may determine the Y ai (based on the determination coefficient R 2 of the interpolation function f i (t) for the distribution of the entire examination values of the examination item X i stored in the examination numerical database.
  • T + 1) and Y bi (T + 1) is selected for each examination item X i as an expected examination value Y i (T + 1) at the next age (T + 1) of the examination item Xi.
  • the biological age prediction device, biological age for using Y i (T + 1) a predetermined angle with respect to the examination item X i in the following ages (T + 1) of the examinee Calculating, and the age, the body predicting device may include the step of transmitting the operation to the in vivo age of the service terminal.
  • the biological age prediction device the screening value Xi of the examination item Xi for the current age (T) of the examinee Receiving (T) for each examination item X i , wherein the biological age predicting device is further configured to determine an average value AVG i (t) of resident registration age (t) of examination values for examination item X i stored in the examination numerical database; Receiving a standard deviation SD i (t) for each screening item X i , wherein the living body age predicting device is a regression equation for each resident registration age (t) of screening values for the screening item X i stored in the screening database; (regression equation) f i (t) is provided or calculated for each screening item X i , after the biological age predicting device reflects the weight to the difference between X i (T) and AVG i (T) , Plus AVG (T + 1) Calculating
  • the weight is SD i (T + 1) / SD i (T), and calculating Y ai (T + 1) for each examination item X i includes X i (T) and AVG i. Calculating the Y ai (T + 1) by multiplying the difference value of (T) by the weight and adding it to AVG i (T + 1), wherein each Y bi (T + 1) is examined.
  • W 2i may be the value of the coefficient of determination (R 2 ) of the regression equation f i (t).
  • the predicted biometric age of next year may be used as a measure of the rate of aging compared to the biometric age of this year. For example, if the age of the living body is faster than the age in resident registration, it may be determined that the aging progresses rapidly.
  • Such data may enable the user of the health examination service to intuitively understand his or her health condition, and the service satisfaction level of the service provider who provides the health examination service by using the examination number prediction device or the biological age prediction device according to the present invention. Can increase.
  • FIG. 1 is a diagram showing the configuration of a medical examination system using a medical examination number prediction device or a biological age prediction device according to the present invention.
  • FIG. 2 is a diagram illustrating a configuration of a health examination system of a form different from that in FIG. 1.
  • 3 to 6 are block diagrams of a diagnosis value predicting apparatus according to an embodiment of the present invention.
  • 7 to 10 are graphs showing the distribution tendency of the average of the screening values by age of resident registration for some screening items stored in the health screening data.
  • 11 to 14 are block diagrams of an apparatus for predicting a living body age according to another embodiment of the present invention.
  • FIG. 15 is a block diagram of a living body age predicting apparatus according to another embodiment of the present invention.
  • this age (T) and the next age (T + 1) appearing in the present specification means a time flow according to a predetermined screening cycle.
  • the next age (T + 1) means next year
  • the next age (T + 1) means three months later.
  • the examination period may coincide with a period in which the medical examination data stored in the examination numerical database are divided over time.
  • the current age (T) and the next age (T + 1) may be any cycle, and are not limited to mean a specific cycle (eg, 1 year).
  • the apparatus 100 for predicting a medical examination operates as a service server 4, and a terminal (not shown) located in a medical examination institution (eg, a hospital) 10 operates as a service client. Since the numerical prediction apparatus 100 and the terminal are connected through a network, the examination numerical prediction apparatus 100 may be geographically separated from the examination institution 10. The terminal of the examination institution 10 transmits the examination value of each examination item of the examinee 1 to the examination number prediction device 100, and in response, the examination for the next age (T + 1) of the examination item. You can be provided with a predictive value for the figures.
  • server of the service server 4 is only given based on being in a server-client relationship in relation to the terminal, and is not limited to the shape of the apparatus, the installation location, and the like.
  • the terminal includes a computer having a LAN interface, a UMPC (Ultra Mobile PC), a workstation, a net-book, a personal digital assistant (PDA), a portable computer, a web tablet, a wireless telephone ( wireless phone, mobile phone, smart phone, portable multimedia player (PMP), portable game machine, digital audio player, digital picture recorder, digital video player ( digital picture player, digital video recorder, one of the various electronic devices that make up a home network, one of the various electronic devices that make up a computer network, or one of the various components that make up a computing system Electronic devices such as the like.
  • UMPC Ultra Mobile PC
  • workstation a net-book
  • PDA personal digital assistant
  • PMP portable game machine
  • digital audio player digital picture recorder
  • digital video player digital picture player, digital video recorder
  • the terminal of the examination institution 10 inputs the next age prediction values of the provided examination items into a predetermined biological age calculation function obtained according to a statistical analysis of the examination item values, thereby obtaining the next biological age of the examinee 1.
  • the health examination report for the examinee 1 may be generated using the predicted and predicted next living age. Refer to Korean Patent Publication No. 2007-0080852 and the like for a method of calculating the living age using the respective screening item screening values.
  • the biometric age prediction apparatus 200 may operate as the service server 4 instead of the examination numerical prediction apparatus 100.
  • the terminal of the examination institution 10 may transmit the examination numerical data for each of the plurality of examination items to the biological age prediction apparatus 200, and receive the next biological age prediction value of the examinee 1 in response. have.
  • the terminal of the examination institution 10 may generate a medical examination report for the examinee 1 using the data received from the service server 4.
  • a database server 6 that manages a checkup numerical value database exists, receives a checkup value from a checkup device 2, and a terminal 5 connected to the database server 6 via a network.
  • the health screening system may be configured in the present form.
  • the terminal 5 may be a medical examination number predicting apparatus 100 or a biological age predicting apparatus 200 according to the present invention.
  • the database server 6 may manage the accumulated checkup values for each checkup item and each checkup age as the health checkup is performed for a large number of checkups over a long period of time.
  • the database server 6 may generate and update an average value and a standard deviation for each age for each examination item.
  • the database server 6 may generate and update a regression equation and its determination coefficient R 2 for each examination item.
  • the database server 6 may provide the terminal 5 with the average value and the standard deviation and the regression equation and its determination coefficient R 2 at the request of the terminal 5.
  • the database server 6 may receive a determination coefficient for the entire diagnosis value of the specific interpolation function, calculate the calculation coefficient, and output the determination coefficient.
  • the health check system may include a numerical value predicting device 100, a biological age predicting device 200, a medical value predicting method, or a biological age.
  • the prediction method can be applied.
  • FIG. 3 is a checkup numerical value predicting device 100 which receives a checkup value of this age T, and outputs a checkup value estimate of the next age T + 1 with reference to the mean value and standard deviation of the checkup value. Shows the configuration.
  • the examination numerical prediction apparatus 100 may include a examination numerical input unit 102, a statistical information receiver 104, and a examination numerical prediction unit 106. Although not shown in FIG. 3, the examination numerical prediction apparatus 100 may further include a network interface for receiving data from an external device or transmitting data to the external device 100. This applies equally to FIGS. 3 to 6 and the same to FIGS. 11 to 14.
  • the statistical information receiving unit 104 determines the average value AVG (T) and standard deviation SD (T) of the first examination item for this age T and the average value of the first examination item for the next age T + 1.
  • AVG (T + 1) and standard deviation SD (T + 1) are provided.
  • the examination value input unit 102 is provided with a examination value X (T) of the first examination item of the examinee for this age T.
  • the examination numerical predictor 106 reflects the weighted value of the difference between X (T) and AVG (T), and adds the weighted value to AVG (T + 1) for the next age (T + 1) of the examinee. 1 Calculate the expected value Y (T + 1) of the examination item. In this case, the examination numerical predictor 106 may calculate Y (T + 1) using Equation 1 below. As shown in Equation 1, the difference between X (T) and AVG (T) is adjusted according to the standard deviation ratio for this age (T) and the next age (T + 1), and AVG (T + Is added to 1). In other words, the standard deviation ratio for this age (T) and the next age (T + 1) is used as a kind of weight for the difference between X (T) and AVG (T).
  • FIG. 4 is a diagnosis value predicting device 100 which generates a mean value and a standard deviation of a diagnosis value at the time of receiving a diagnosis value of this age T and outputs an estimate of a diagnosis value of a next age T + 1 (100). Shows a configuration.
  • the examination value prediction apparatus 100 shown in FIG. 4 reflects the latest diagnosis value database in real time to predict the diagnosis value.
  • a check value input by the check value predicting device 100 is added to a check value database and used for predicting the next check value.
  • the apparatus 100 for predicting a diagnosis value may further include a diagnosis value storage unit 110 and a statistical information real-time generator 108 as compared to that shown in FIG. 3.
  • the examination value storage unit 110 stores a examination value database.
  • the examination value storage unit 110 may add and store X (T) provided by the examination value input unit 102 to an existing examination number database.
  • the statistical information real-time generating unit 108 in response to the examination numerical input unit being provided with X (T), from the examination numerical data stored in the examination numerical database AVG (T), AVG ( T + 1), the standard deviation SD (T), and SD (T + 1) are calculated and provided to the statistical information receiver 104.
  • FIG. 5 receives a checkup value of this age T, generates a checkup numerical predictive model using average values of the checkup value, and refers to a predicted value according to the checkup numerical predictive model of a next age.
  • prediction apparatus 100 which outputs the examination numerical value estimated value of age T + 1 is shown.
  • the examination numerical prediction apparatus 100 may include a examination numerical input unit 102, a statistical information receiver 104, an average predictive model generator 105, and a examination numerical predictor 107. have.
  • the examination numerical input unit 102 and the statistical information receiving unit 104 operate similarly to those described with reference to FIG. 3. However, the statistical information receiver 104 provides the average prediction model AVG (t) for each age to the average prediction model generator 105.
  • the mean prediction model generator 105 generates an interpolation function f (t) for AVG (t) using extrapolation.
  • the average prediction model generator 105 may use polynomial extrapolation.
  • the interpolation function by extrapolation may not coincide with AVG (t). That is, AVG (t) and f (t) may not coincide.
  • the examination numerical prediction apparatus 100 shown in FIG. 5 predicts the examination numerical value differently from the examination numerical prediction apparatus shown in FIGS. 3 to 4.
  • the examination numerical predictor 107 of FIG. 5 may calculate Y (T + 1) using Equation 2 below.
  • FIG. 6 is a prediction according to a diagnosis value prediction model generated by using a diagnosis value of this age T, the first prediction value referring to the mean value and the standard deviation of the diagnosis value and the mean value of the diagnosis value.
  • prediction apparatus 100 which outputs the examination numerical expectation value of the next age (T + 1) using all the 2nd prediction values which referred the value is shown.
  • the examination numerical prediction apparatus 100 shown in FIG. 6 replaces the examination numerical prediction unit 107 shown in FIG. 5 with the first examination numerical prediction unit 112, the second examination numerical prediction unit 114, and the prediction. And a value adjusting unit 116.
  • the first examination numerical predicting unit 112 reflects the weight of the difference between X (T) and AVG (T), and adds the weight to AVG (T + 1) to the next age (T + 1) of the examinee. Compute a first expected checkpoint value Y a (T + 1) of the first check item. Y a (T + 1) is calculated using Equation 1 above.
  • the second examination numerical predictor 114 reflects the weight to the difference between X (T) and f (T), and then adds f (T + 1) to the next age of the examinee (T + 1). Compute a second expected checkup value Y b (T + 1) of the first check item for. Y b (T + 1) is calculated using Equation 2 above.
  • the predicted value adjusting unit 116 uses Y a (T + 1) and Y b (T + 1) to predict an expected examination value Y (T) of the first examination item for the next age (T + 1) of the examinee. Compute +1).
  • the prediction value adjusting unit 116 calculates Y (T + 1) using Equation 3 below.
  • W 2 may be a value that is determined based on the value of the determination coefficient (R 2 ) of the interpolation function f (t) for the distribution of the entire first examination item examination value stored in the examination numerical database.
  • the determination coefficient R 2 may be provided from the database server 6.
  • the coefficient of determination (R 2 ) is a value representing the goodness of fit of the interpolation function f (t). Since a calculation method is widely known in relation to a regression analysis methodology, a detailed description thereof will be omitted. At this time, using the product of a predetermined weight to R 2 as W 2, or R 2 may be the same as W 2. 7 to 10 are graphs showing the distribution tendency of the average of the screening values by age of resident registration for some screening items stored in the health screening data. In the case where the distribution of the average value is irregular as shown in FIG. 9, it is more accurate to calculate Y (T + 1) based on the interpolation function f (t) than based on the average value.
  • the biological age prediction apparatus 200 predicts and outputs a biological age value of the next age T + 1 using Y (T + 1).
  • FIG. 11 is a prediction according to a diagnosis value prediction model generated by using a diagnosis value of this age T, a first prediction value referring to an average value and a standard deviation of the diagnosis value, and an average value of the diagnosis value.
  • a checkout estimate for the next age (T + 1) is calculated, the operation is repeated for each input checkup value, and the calculated checkpoint estimates for each checkup item are used.
  • the configuration of the biological age predicting apparatus 200 for outputting the biological age predictive value of the next age T + 1 is shown.
  • the examination numerical prediction model may be, for example, an interpolation function generated using average values.
  • the second prediction value may be more heavily reflected than the first prediction value as the determination coefficient R 2 of the examination numerical prediction model is closer to one.
  • the biometric age predicting apparatus 200 of FIG. 11 further includes a biometric age predicting unit 206, and the biometric age predicting unit 206 uses Y i (T + 1) calculated for each of the examination items X i . The living body age is then calculated for the next age (T + 1) of the examinee 1.
  • FIG. 12 receives a checkup value of this age T, generates a first prediction value referring to the mean value and standard deviation of the checkup value, and a regression equation that is a regression analysis model of all checkup numerical data in the checkup numerical database.
  • a regression equation that is a regression analysis model of all checkup numerical data in the checkup numerical database.
  • the configuration of the biometric age prediction apparatus 200 that outputs the biometric age prediction value of the next age (T + 1) using the calculated examination item-specific examination numerical estimates is shown.
  • the second prediction value may be more heavily reflected than the first prediction value as the determination coefficient R 2 of the regression equation approaches 1.
  • the biological age prediction apparatus 200 may include a regression model generator 203 instead of the average prediction model generator 205 of FIG. 11.
  • the regression model generator 203 may generate a regression equation or may be provided from the database server 6 and used instead of the interpolation function described with reference to FIG. 11.
  • the regression equation is a formula generated as a result of regression analysis of the entire examination value for the examination item X i stored in the examination numerical database. Unlike the interpolation function, which is generated only with an average value, the regression equation is generated by using the entire examination values of each examinee. Therefore, based on the regression equation Y i (T + 1) if the calculated values, based on the interpolation function Y i (T + 1) calculated in comparison with the case of calculating the value of Y i (T + 1) Higher accuracy of the value can be expected.
  • the prediction value adjusting unit 216 of FIG. 12 may be provided with the determination coefficient R 2 of the regression equation from the database server 6.
  • FIG. 13 to FIG. 14 are screens for predicting a numerical value generated by using a first predicted value referring to the mean value and standard deviation of the check value and the mean value of the check value.
  • One of the second prediction values referring to the prediction value according to the present invention is selected as an examination value estimate of the next age (T + 1), the operation is repeated for each input diagnosis value, and the calculated diagnosis value estimates for each examination item are calculated.
  • the configuration of the living body age predicting device 200 which outputs the living body age predicting value of the next age (T + 1) is shown.
  • the examination numerical prediction model may be, for example, an interpolation function generated using average values.
  • the second prediction value may be more heavily reflected than the first prediction value as the determination coefficient R 2 of the examination numerical prediction model is closer to one.
  • the biological age prediction apparatus 200 illustrated in FIGS. 13 to 14 sets one of the first prediction value Y ai (T + 1) and the second prediction value Y bi (T + 1) to Y i (T + 1).
  • the biometric age prediction apparatus 200 shown in FIG. 11 differs from calculating Y i (T + 1) by summing and applying weights to the first and second prediction values, respectively. Is similar.
  • Y ai (T + 1) and Y bi (T + 1) is assigned to each examination item X i with the expected examination value Y i (T + 1) at the next age (T + 1) of the examination item Xi. Is selected.
  • a second prediction value Y bi (T + 1) is selected as Y i (T + 1).
  • the first predicted value Y ai (T + 1) may be selected as Y i (T + 1).
  • FIG. 14 illustrates operations of the first diagnosis numerical value predicting unit 212, the second diagnosis numerical predicting unit 214, and the diagnosis numerical selecting unit 210 of FIG. 13 integrated into the diagnosis numerical predicting unit 208.
  • FIGS. 3 to 6 and 11 to 14 may refer to software or hardware such as a field-programmable gate array (FPGA) or an application-specific integrated circuit (ASIC). .
  • the components are not limited to software or hardware, and may be configured to be in an addressable storage medium or may be configured to execute one or more processors.
  • the functions provided in the above components may be implemented by more detailed components, or may be implemented as one component that performs a specific function by combining a plurality of components.
  • 3 to 6 and 11 to 14 may include at least one processor, a memory connected to the processor, a system bus connected to the memory, at least one storage device connected to the system bus, and a system bus connected to the system bus. It may be implemented as a system including at least one network interface.
  • FIG. 15 is a flowchart of a method of predicting a living body age according to another embodiment of the present invention.
  • the biological age prediction method illustrated in FIG. 15 may be performed by the biological age prediction apparatus 200 illustrated in FIGS. 11 to 14, but is not necessarily limited to the biological age prediction apparatus 200.
  • the subject to perform is the biological age predicting apparatus 200.
  • the biological age predicting apparatus 200 receives a checkup value Xi (T) of a check item Xi for each check item X i for each check item X i (S100).
  • the biological age predicting apparatus 200 checks the average value AVG i (t) and the standard deviation SD i (t) by the resident registration age (t) of the examination values for the examination item X i stored in the examination numerical database, respectively.
  • the item X i is provided from the database server 6 (S102).
  • the biological age predicting apparatus 200 calculates the first expected value Y ai (T + 1) and the second estimated value Y bi (T + 1) of the examination value X i (T) for the next age.
  • Y ai (T + 1) may be calculated by adding weights to the difference between X i (T) and AVG i (T), and then summing to AVG (T + 1) (S108).
  • Y bi (T + 1) generates an interpolation function f i (t) of AVG i (t) (S104), and then reflects the weights to the difference between X i (T) and f i (T). Then, it can be calculated by adding to f (T + 1).
  • the biological age predicting apparatus 200 may calculate Y i (T + 1) using both Y ai (T + 1) and Y bi (T + 1). At this time, the value of the coefficient of determination (R 2 ) of the interpolation function f i (t) for the distribution of the whole examination value of the examination item X i stored in the examination number database is used as a weight for Y bi (T + 1). Can be.
  • the biological age prediction apparatus 200 may select one of Y ai (T + 1) and Y bi (T + 1) as Y i (T + 1) (S110).
  • the determination coefficient (R 2 ) of the interpolation function f i (t) for the distribution of the whole examination value of the examination item X i stored in the examination number database may be used as a selection criterion.
  • Y bi (T + 1) is not an interpolation function of AVG i (t), but a regression equation according to resident registration age (t) of the screening values for screening items X i stored in the screening database. It can also be calculated using the regression equation.
  • the regression equation may be received by the biological age predicting apparatus 200 by querying the database server 6.
  • the reference or weight used in selecting or calculating Y i (T + 1) is not a coefficient of determination of the interpolation function, but a coefficient of determination of the regression equation.
  • the biological age predicting apparatus 200 calculates the biological age value expected at the next age T + 1 using the values of Y i (T + 1) (S112).
  • the biological age predicting apparatus 200 transmits the biological age value to a device such as a service terminal (S114).

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  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Biomedical Technology (AREA)
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  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
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Abstract

L'invention concerne un appareil et une méthode de prévision de la valeur de l'examen physique de l'année suivante d'un organisme en utilisant l'examen physique de l'année en cours ainsi que de prévision du bio-âge de l'année suivante de l'organisme en utilisant la valeur prévue de l'examen physique de l'année suivante. Selon un mode de réalisation, l'appareil de prévision de la valeur de l'examen physique comprend : une partie de réception d'informations statistiques permettant de recevoir la valeur moyenne AVG(T) et l'écart type SD(T) d'un premier élément d'examen pour l'âge de l'année en cours (T) et la valeur moyenne AVG(T+1) et l'écart type SD(T+1) d'un premier élément d'examen pour l'âge de l'année suivante (T+1); une partie de saisie de valeur examinée permettant de recevoir la valeur examinée X(T) du premier élément d'examen d'un sujet examiné pour l'âge de l'année en cours (T); et une partie de prévision de valeur examinée permettant de calculer la valeur prévue Y(T+1) du premier élément d'examen du sujet examiné pour l'âge de l'année suivante (T+1) en appliquant une pondération à la différence entre X(T) et AVG(T) et en ajoutant le résultat de celle-ci à AVG(T+1). Selon le mode de réalisation, l'appareil de prévision de la valeur de l'examen physique calcule la valeur prévue d'un élément d'examen d'un sujet examiné en appliquant une pondération à la différence entre la valeur examinée et la moyenne pour l'âge de l'année en cours et en ajoutant le résultat de celle-ci à la moyenne examinée pour l'âge de l'année suivante, en faisant l'hypothèse que la différence entre la valeur examinée et la moyenne du sujet examiné pour l'âge de l'année en cours est aussi maintenue de façon similaire pour l'âge de l'année suivante.
PCT/KR2014/001236 2013-04-22 2014-02-14 Appareil et méthode de prévision de bio-âge Ceased WO2014175542A1 (fr)

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KR102784252B1 (ko) 2021-12-03 2025-03-21 주식회사 메디에이지 이상지질혈증 검사 유무와 상관없이 일반건강검진 임상지표를 이용한 생체나이 측정 및 이를 이용한 의료 이용률과 의료비 예측 방법 및 시스템
KR102808739B1 (ko) 2021-12-03 2025-05-21 주식회사 메디에이지 이상지질혈증 검사 유무와 상관없이 일반건강검진 임상지표를 이용한 생체나이 측정 및 노화 관련 질병 발생 위험도 예측 방법 및 시스템
KR20230083711A (ko) 2021-12-03 2023-06-12 주식회사 메디에이지 생체나이와 유전자 검사, 영양 설문에 기반한 맞춤형 영양 성분 추천 방법 및 시스템
KR20230083981A (ko) 2021-12-03 2023-06-12 주식회사 메디에이지 가족력과 생활습관을 반영한 생체나이 기반 개별 암 발생 위험도 예측 방법 및 시스템
KR102783714B1 (ko) 2022-07-21 2025-03-21 주식회사 로그미 건강나이를 예측하는 장치 및 방법
KR102854995B1 (ko) 2023-01-02 2025-09-04 주식회사 온택트헬스 건강 나이를 결정하기 위한 방법 및 장치
KR20250042903A (ko) 2023-09-20 2025-03-28 (주)비바이노베이션 귀 생체 나이 예측 기반의 의료 지원 서비스 제공 시스템 및 방법
KR20250042904A (ko) 2023-09-20 2025-03-28 (주)비바이노베이션 갑상선 생체 나이 예측 기반의 의료 지원 서비스 제공 시스템 및 방법

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JPWO2017073713A1 (ja) * 2015-10-30 2018-08-09 Ｎｅｃソリューションイノベータ株式会社 血糖値予測装置、血糖値予測方法及びコンピュータ読み取り可能な記録媒体
WO2019147725A1 (fr) * 2018-01-23 2019-08-01 Spring Discovery, Inc. Procédés et systèmes permettant de déterminer l'âge biologique d'échantillons
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CN105144174A (zh) 2015-12-09

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