WO2022239579A1 - Information processing device, estimation method, and estimation program - Google Patents

Abstract

Provided is an information processing device for estimating the possibility of a user to develop diabetes in 10 years. This information processing device is provided with: a reception unit that receives input of the age of a user, the presence or absence of smoking habit, and urine pH as user information relating to the user; an estimation unit that estimates the possibility of the user to develop diabetes on the basis of the user information; and an output unit that outputs information indicating the possibility of the user to develop diabetes estimated by the estimation unit.

Description

Information processing device, estimation method, and estimation program

The present invention relates to an information processing device for estimating the possibility of diabetes, its estimation method, and an estimation program.

Conventionally, it is known that a user's degree of obesity is related to diabetes. Patent Literature 1 discloses a health condition estimation device that estimates a user's health condition based on the user's degree of obesity.

JP 2020-166441 A

By the way, there is a demand for further improvement in the accuracy of estimating the possibility that a user will develop diabetes, and methods other than estimation based on the degree of obesity are also in demand.

Therefore, an object of the present invention is to provide an information processing device, an estimation method, and an estimation program that can estimate the possibility that a user will develop diabetes using a method different from the conventional method.

The information processing apparatus according to the present invention includes a reception unit that receives input of the user's age, the presence or absence of a smoking habit, and urine pH as user information about the user; and an output unit configured to output information indicating the possibility of the user having diabetes estimated by the estimation unit.

In the above information processing device, the estimation unit may estimate the possibility that the user will develop diabetes based on the presence or absence of smoking habits for each predetermined range of urine pH according to the age of the user.

In the above information processing device, the user information may further include the user's degree of obesity.

In the above information processing device, the estimation unit may estimate the possibility that the user will develop diabetes according to the degree of obesity relative to a predetermined threshold value and whether or not the user has a smoking habit for each predetermined range of urine pH. .

In the above information processing device, comprising a storage unit for storing disease possibility information indicating the possibility of contracting diabetes according to the degree of obesity with respect to a predetermined threshold value and the presence or absence of a smoking habit for each predetermined range of urine pH, The estimation unit may estimate the possibility that the user will develop diabetes based on the user information and the disease possibility information.

In the above information processing device, the storage unit stores the disease possibility information for each age of the user within a predetermined range, and the estimation unit determines whether the user is diagnosed with diabetes based on the disease possibility information according to the age of the user. It is also possible to estimate the possibility of

In the above information processing device, the estimating unit compares the user with other users of the same age who have a degree of obesity below a predetermined threshold and who do not have a smoking habit, and compares the user with diabetes. It is also possible to estimate the multiplier indicating the possibility that the user will develop diabetes.

In the above information processing device, the estimation unit may estimate the possibility that the user will develop diabetes after a predetermined number of years.

The above information processing apparatus may include a proposal unit that makes a proposal to prevent the user from developing diabetes based on the possibility that the user will develop diabetes estimated by the estimation unit.

In the information processing device, the communication unit is attached to the toilet bowl and communicates with the measuring device that measures pH, and the reception unit receives the pH measured by the measurement device received by the communication unit as the urine pH of the user. may be

In the above information processing device, the communication unit receives specific information specifying a user corresponding to the urine pH measured by the measuring device, and the output unit outputs information indicating the possibility of diabetes of the user indicated by the specific information. It may be transmitted to the terminal.

In the above information processing device, the user may be male.

In the above information processing device, the reception unit further receives morbidity information indicating that the user has diabetes, and the information processing device, based on the morbidity information and the user information of the user corresponding to the morbidity information, An updating unit that updates the disease possibility information may be provided.

The estimation method according to the present invention is an estimation method in which a computer estimates the possibility that a user will develop diabetes, and the user's age, the presence or absence of a smoking habit, and the urine pH are input as user information about the user. a receiving step of receiving, an estimating step of estimating the possibility of the user suffering from diabetes based on the user information, an outputting step of outputting information indicating the possibility of the user suffering from diabetes estimated by the estimating step, including.

The estimating program according to the present invention is provided in a computer with a reception function that receives input of the user's age, the presence or absence of a smoking habit, and urine pH as user information about the user, and based on the user information, the user is diagnosed with diabetes. and an output function for outputting information indicating the possibility that the user will develop diabetes, which is estimated by the estimation function.

The information processing device, estimation method, and estimation program according to the present invention can estimate the possibility that a user will develop diabetes after a predetermined number of years. Therefore, when the estimation result indicates that the possibility of developing diabetes is high, for example, preventive measures can be taken from the present time to reduce the likelihood of developing diabetes.

1 is a block diagram showing a configuration example of an information processing apparatus according to a first embodiment; FIG. FIG. 5 is a diagram showing an example of a first control table for estimating the possibility of developing diabetes according to Example 1; 4 is a flow chart showing an example of the operation of the information processing apparatus according to the first embodiment; FIG. 11 is a block diagram showing a configuration example of an information processing apparatus according to a second embodiment; FIG. 12 is a diagram showing an example of a second control table for estimating the possibility of developing diabetes according to Example 2; 9 is a flow chart showing an operation example of the information processing apparatus according to the second embodiment; FIG. 11 is a system diagram showing a configuration example of a diabetes estimation system for estimating diabetes according to Example 3; FIG. 11 is a block diagram illustrating a configuration example of an information processing apparatus according to a third embodiment; FIG. 11 is a block diagram showing a configuration example of a measuring device according to Example 3; FIG. 12 is a block diagram showing a configuration example of a user terminal according to Example 3; 4 is a data conceptual diagram showing a data configuration example of user information; FIG. FIG. 4 is a sequence diagram showing an example of exchanges between the measuring device, the information processing device, and the user terminal in the diabetes estimation system; FIG. 13 is a flow chart showing an operation example of the measurement device for realizing the exchange shown in FIG. 12; FIG. 13 is a flow chart showing an operation example of the information processing device for realizing the exchange shown in FIG. 12; 13 is a flow chart showing an operation example of a user terminal for realizing the exchange shown in FIG. 12; FIG. 10 is a diagram showing a display example of an estimation result on a user terminal;

An embodiment of the present invention will be described below with reference to the drawings.

<Embodiment 1>
<Configuration>
FIG. 1 is a block diagram showing a configuration example of an information processing apparatus 100 according to the present invention.

The information processing apparatus 100 according to Embodiment 1 is a computer that can estimate the possibility that a user will develop diabetes 10 years from now, based on the user's urine pH, smoking habit, and age. Further, the information processing apparatus 100 may be a computer that can suggest improvements in lifestyle habits and the like for preventing diabetes in 10 years from now, based on the possibility that the user will have diabetes in 10 years from now. A detailed description will be given below.

As shown in FIG. 1, the information processing device 100 includes a communication unit 110, an input unit 120, a control unit 130, a storage unit 140, and an output unit 150.

The communication unit 110 is a communication interface having a function of communicating with an external device (not shown in FIG. 1) via a network. As an example, the external device may be various communication terminals such as a user's smartphone, mobile phone, tablet terminal, PC, notebook PC, etc. that estimate the possibility of developing diabetes in 10 years, and the user's urine pH ( It may be a measuring device for measuring uric acid level), or an information processing device provided in a hospital or the like that holds information on a user's urinary pH and degree of obesity. Communication unit 110 transmits the received information to control unit 130 . Further, the communication unit 110 transmits information instructed by the control unit 130 to the instructed destination.

The input unit 120 is an input interface that receives input from the operator of the information processing device 100 or the like. The input unit 120 may be implemented by, for example, a mouse, keyboard, touch panel, or the like, but is not limited to these. The input unit 120 may be, for example, a microphone that receives voice input. The input unit 120 transmits input contents to the control unit 130 . The input unit 120 may receive, for example, the user's urinary pH, the presence or absence of a smoking habit, the age, and the like, as information regarding the user for estimating the possibility of developing diabetes in 10 years.

The control unit 130 is a processor having a function of controlling each unit of the information processing device 100 . The control unit 130 uses various programs and data stored in the storage unit 140 to implement the functions that the information processing apparatus 100 should perform. The control unit 130 has an estimation unit 131 as a function to be performed. Also, the control unit 130 may include a proposal unit 132 .

The estimation unit 131 estimates the possibility that the user will develop diabetes 10 years from now, based on the user's age, urine pH, and whether or not the user has a smoking habit. The estimating unit 131 reads out the disease possibility information 141 stored in the storage unit 140, and estimates the possibility that the user will develop diabetes 10 years later, corresponding to the user's age, urine pH, and smoking habit. Get an index value that indicates . Then, based on the acquired index value, the possibility that the user will develop diabetes 10 years from now is estimated.

The estimating unit 131 may estimate how likely the user will develop diabetes 10 years from now, compared to other users. That is, the estimation unit 131 may output relative information compared with others as information indicating the possibility that the user will develop diabetes in 10 years. The estimating unit 131 is basically a user of the same age as the user, and may estimate how likely it is to get diabetes compared to a user of the type who is least susceptible to diabetes. A user who becomes a person does not have to be a user of the same age. However, it can be said that the index estimated by the estimation unit 131 is easier for the user to understand when compared with users of the same age.

Based on the estimation result estimated by the estimation unit 131, the proposal unit 132 proposes measures for preventing the user from developing diabetes in 10 years. The proposing unit 132 may, for example, propose measures for preventing diabetes based on the estimation result estimated by the estimating unit 131 . As an example, although not shown, the proposing unit 132 associates the index value range estimated by the estimating unit 131 with preventive measures to be taken by the user according to the specified index value range in the storage unit 140. By storing the preventive table, the content to be proposed may be specified. Alternatively, the storage unit 140 stores in advance a learning model that learns the relationship between an index value indicating the possibility of developing diabetes in 10 years and preventive measures to be taken to prevent diabetes, By inputting the index value estimated by the estimation unit 131 into this learning model, the contents to be proposed may be specified. There may be multiple proposal contents. Specific examples of the content of the proposal include, but are not limited to, promoting exercise, improving lifestyle habits, and improving diet. Further, the proposing unit 132 may execute a proposal when the index value indicating the estimation result estimated by the estimating unit 131 is equal to or greater than a predetermined threshold. As an example, the proposing unit 132 may propose exercise and exercise time to the user according to the index value indicating the estimation result by the estimating unit 131 .

The storage unit 140 is a storage medium having a function of storing various programs and data required for the information processing apparatus 100 to operate. The storage unit 140 may be realized by, for example, a HDD (Hard Disc Drive), SSD (Solid State Drive), flash memory, etc., but is not limited to these. Moreover, the memory|storage part 140 may contain ROM and RAM. The storage unit 140 stores a program for estimating the possibility that the user will develop diabetes 10 years from now, based on the information about the user input to the input unit 120 by the estimating unit 131, A program may be stored for suggesting measures to deter the possibility of contracting the disease. The storage unit 140 also stores disease possibility information 141 . The disease possibility information 141 is a first control table referred to for estimating the possibility of developing diabetes 10 years from now based on the user's age, urine pH, and smoking habit. Details of the disease possibility information 141 will be described later.

The output unit 150 has a function of outputting information specified by the control unit 130 . The output unit 150 may be realized by a monitor, a speaker, or the like provided in the information processing apparatus 100 or connected to the information processing apparatus 100 . The output unit 150 may output a character string or an image, or may output a sound. The output unit 150 has a function of outputting the estimation result estimated by the estimation unit 131 and the content of the proposal proposed by the proposal unit 132 .

The above is a configuration example of the information processing apparatus 100 .

<Data>
FIG. 2 is a data conceptual diagram showing a data configuration example of the disease possibility information 141. As shown in FIG. As described above, the disease possibility information 141 is a table referred to by the control unit 130 in order to estimate the possibility that the user will develop diabetes ten years from now.

As shown in FIG. 2, the disease possibility information 141 includes, as age, the range of urine pH according to each generation, and the likelihood of developing diabetes 10 years later according to the presence or absence of smoking habit in each range. It is information that defines the indicators of In the case of the disease possibility information 141 shown in FIG. 2, an example is shown in which age is divided into less than 40 years old, 40 to 50 years old, and 51 years old and over. Also, an example is shown in which the urine pH is divided into four categories of 6.5 or more, 6.0, 5.5, and 5.0 or less. Basically, people with lower urine pH are more likely to develop diabetes, and people with higher urine pH are less likely to develop diabetes than people with low urine pH.

In the case of the disease possibility information 141 shown in FIG. 2, as an example, a user whose age is between 40 and 50, who has a urine pH of 5.0 or less, and who has a smoking habit of 10 years from now The index value indicating the possibility of developing diabetes is "2.5".

The index value indicating the possibility of developing diabetes 10 years later in the disease possibility information 141 shown in FIG. 2 is a reference pattern for other cases. It is an index that shows how high the possibility of getting diabetes is.

In the case of FIG. 2, based on the user whose age is “under 40”, whose urine pH is “6.5 or more”, and whose smoking habit is “none”, in the other cases (other users under 40) ), and the index value is "1.0", so it can be understood that it is used as a standard. For example, the index value indicating the possibility that a user whose age is “under 40”, whose urine pH is “6.0”, and whose smoking habit is “yes” will develop diabetes in 10 years is “5. 3”. That is, a user whose age is “under 40”, whose urine pH is “6.0”, and whose smoking habit is “yes” is “under 40” and whose urine pH is “6.5 or higher”. , means that users with a smoking habit of "no" are "5.3" times more likely to develop diabetes after 10 years. In such a case, the estimating unit 131 also determines that the user is "under 40" in age, has a urine pH of "6.0", and has a smoking habit of "yes." 5.3 times more likely than a person with a urine pH of 6.5 or higher and no smoking habit to have diabetes in 10 years." can be done.

As another example, if the target user is "42 years old", has a urine pH of "5.5", and does not have a smoking habit of "no", then the comparison target is , age 40 to 50, urine pH 6.5 or higher, and no smoking habit. As a result, the estimation unit estimates that the user is 2.1 times more likely to develop diabetes 10 years later than a person of the same age who has a urine pH of 6.5 or higher and who does not have a smoking habit. Thus, the estimating unit 131 basically estimates the possibility that the user will develop diabetes by comparing with people of the same age who are least likely to develop diabetes.

The index values and urine pH threshold values shown in FIG. It can be identified by collecting the user's past information (urine pH and information on whether or not he/she has a smoking habit) from a year ago. In addition, in FIG. 2, the urine pH is set to 0.5 increments, but this is an example. The illustrated column for urine pH 6.0 may be, for example, 5.8 to 6.0, and the column for urine pH 5.5 may be, for example, 5.1 to 5.7. good too. For example, when the measured urine pH of the user is measured in increments of 0.1, when using the disease possibility information 141 in FIG. 2, the urine pH shown in FIG. Close values may be identified as applicable to the user. For example, when the user's urine pH is "6.1", the index value corresponding to the urine pH of "6.0" in the disease possibility information 141 may be used.

With the disease possibility information 141, the estimating unit 131 can estimate the possibility that the user will develop diabetes 10 years later. , it is possible to estimate how likely a person is to suffer from diabetes. Here, it is assumed that the possibility of developing diabetes 10 years from now is estimated. If you collect past information (urine pH and information on the presence or absence of smoking habits) of users who do not have diabetes five years ago (information on urine pH and smoking habits), five years later Disease possibility information 141 for estimating the possibility of contracting diabetes can be generated.

<Action>
FIG. 3 is a flow chart showing an operation example in estimation processing by the information processing apparatus 100 .

As shown in FIG. 3, the information processing apparatus 100 receives input of information about the user (step S301). Here, the information about the user is information on the user's age, urine pH, and whether or not he or she has a smoking habit. The information processing apparatus 100 may accept direct input from the user via the input unit 120, or receive information via communication from another device, such as a user terminal held by the user, via the communication unit 110. It may be accepted by Communication unit 110 or input unit 120 transmits the received information about the user to control unit 130 .

When the information about the user is received, the estimating unit 131 of the control unit 130 refers to the disease possibility information 141 based on the received user's age, urine pH, and smoking habit, and determines whether the user will have diabetes in 10 years. is estimated (step S302). Then, the estimation unit 131 outputs the estimated estimation result via the output unit 150 (step S304). The output of the estimation result by the output unit 150 may be output as an image or a character string on the monitor of the information processing device 100, or may be output as a voice from the speaker of the information processing device 100, or the communication unit 110. It may also be the output by transfer to another device via the . Also, the estimation unit 131 transmits the estimated result to the proposal unit 132 .

The proposing unit 132 proposes a preventive measure for preventing the user from developing diabetes based on the estimation result of the possibility that the user will develop diabetes transmitted from the estimating unit 131 (step S304), and ends the process. The proposal unit 132 outputs the proposed preventive measures via the output unit 150 . The proposal by the proposal unit 132 may be output in any form of display of an image or a character string, output by voice, or information transfer from another device, similarly to the output of the estimation result by the estimation unit 131 .

<Summary of Embodiment 1>
The inventors have found that a user's age, urinary pH, and whether or not they have a smoking habit greatly contribute to whether or not a user will suffer from diabetes. Conventionally, it is known that a user's degree of obesity is related to diabetes. The inventors have invented the information processing apparatus 100 that can estimate the possibility of a user suffering from diabetes from information related to diabetes. According to the information processing apparatus 100, it is possible to estimate the possibility that the user will develop diabetes after a predetermined number of years (for example, 10 years). In addition, the information processing apparatus 100 can propose measures for reducing the possibility of the user suffering from diabetes due to the suggestion unit, and can contribute to the user's health.

<Embodiment 2>
In the first embodiment, the information processing apparatus 100 estimates the possibility that the user will develop diabetes 10 years from now based on the user's age, urine pH, and smoking habit. In the second embodiment, the information processing apparatus 100 uses the user's obesity level (BMI: Body Mass Index) in addition to the user's age, urine pH, and whether or not he or she has a smoking habit. Estimate the likelihood of developing diabetes in years to come. Conventionally, the degree of obesity of the user is considered to be highly related to diabetes, and by estimating the possibility of developing diabetes in 10 years by taking into account BMI, the accuracy is higher than in the first embodiment. An information processing device that performs estimation can be provided.

FIG. 4 is a block diagram showing a configuration example of an information processing device 400 according to the second embodiment. As shown in FIG. 4 , the information processing device 400 includes a communication section 410 , an input section 420 , a control section 430 , a storage section 440 and an output section 450 . The control unit 430 also includes an estimation unit 431 and a proposal unit 432 , and the storage unit 440 stores disease possibility information 441 . Since each part of the information processing apparatus 400 operates in the same manner as each part having the same name as the information processing apparatus 100 shown in the first embodiment, differences from the first embodiment will be explained in the second embodiment.

The communication unit 410 or the input unit 420 receives input of the user's obesity level (BMI value) in addition to the user's age, urine pH, and smoking habit as information about the user, and transmits the input to the control unit 430. .

Further, the disease possibility information 441 stored in the storage unit 440 is based on the user's age, urine pH, the presence or absence of smoking habit, and the user's degree of obesity. It is a second control table for estimating the possibility of doing. Details of the disease possibility information 441 will be described later.

The estimating unit 431 estimates the possibility that the user will develop diabetes 10 years from now, based on the user's age, urine pH, and smoking habit, as well as the user's degree of obesity. The estimation method itself by the estimation unit 431 is the same as that of the estimation unit 131 shown in the first embodiment.

As described above, the information processing apparatus 400 differs from the information processing apparatus 100 depending on whether or not information on the degree of obesity of the user is used.

<Data>
FIG. 5 is a data conceptual diagram showing a data configuration example of the disease possibility information 441 according to the second embodiment. As can be seen by comparing the disease possibility information 441 shown in FIG. 5 with the disease possibility information 141 shown in FIG. 2, it can be understood that the index values are classified by BMI. That is, as shown in FIG. 5, in the disease possibility information 441, the BMI value of 25 is used as a threshold, and the indices are further divided.

As shown in FIG. 5, the disease possibility information 441 is an index indicating the possibility of developing diabetes according to the user's age range, urinary pH range, obesity degree range, and smoking habit. It is information with a defined value.

As shown in FIG. 5, the disease possibility information 441 shows an example in which the age of the user is divided into under 40, 40 to 50, and over 50 years old. In addition, an example is shown in which the urine pH is divided into four categories of 6.5 or more, 6.0, 5.5, and less than 5.0. Basically, people with lower urine pH are more likely to develop diabetes, and people with higher urine pH are less likely to develop diabetes than people with low urine pH. In addition, in the disease possibility information 441, index values are set with 25 as the boundary for BMI.

In the case of FIG. 5, when the age of the target user is under 40, the age is "under 40", the urine pH is "6.5 or more", the BMI is "under 25", and the smoking habit is Based on the user who answered "none", it indicates whether there is a high possibility of suffering from diabetes in other cases, and since the index value is "1.0", it can be understood that it is used as a reference. . For example, a user whose age is “under 40”, whose urine pH is “6.0”, whose smoking habit is “yes”, and whose BMI is “less than 25” may develop diabetes in 10 years. The index value indicating the sex is "3.4". That is, a user whose age is “under 40”, whose urine pH is “6.0”, whose BMI is “under 25”, and whose smoking habit is “yes” is “under 40” and has a urine pH of “6.0”. is 3.4 times more likely to develop diabetes 10 years later than users with a BMI of '6.5 or more', a BMI of 'less than 25', and a smoking habit of 'no'. In such a case, the estimating unit 131 also detects that the user is "under 40" in age, has a urine pH of "6.0", has a BMI of "less than 25", and has a smoking habit of "has". users are 3.4 times more likely to have diabetes 10 years later than non-smokers of the same age who have a urine pH of 6.5 or higher and a BMI of less than 25. Such content can be output as an estimation result.

As another example, if the target user is "56 years old", the urine pH is "4.4", the BMI is "32", and the smoking habit is "none", the estimated Part 431 is 2.3 times more likely than a person whose age is "50 years old or older", whose urine pH is "6.5" or higher, whose BMI is "less than 25", and whose smoking habit is "no". are likely to have diabetes 10 years later.

The index value, urine pH threshold, and BMI threshold shown in FIG. It can be identified by collecting past information (urine pH, smoking habit, and BMI information) of users who do not smoke 10 years ago. In the example shown in FIG. 5, the BMI threshold is set to 25, but this is an example and is not limited to 25. For example, the BMI threshold may be set to 30. Each index value shown in FIGS. 2 and 5 is an example, and varies depending on the number of samples. The larger the number of samples, the more accurate index values can be calculated.

With the disease possibility information 441, the estimation unit 431 can estimate the possibility that the user will develop diabetes 10 years from now. Here, it is assumed that the possibility of developing diabetes 10 years later is estimated. If you collect past information (urine pH and information on the presence or absence of smoking habits) of users who do not have diabetes five years ago (information on urine pH and smoking habits), five years later Disease possibility information 441 for estimating the possibility of contracting diabetes can be generated.

<Action>
FIG. 6 is a flowchart showing an operation example of estimating the possibility that the user will develop diabetes ten years from now by the information processing apparatus 400 .

As shown in FIG. 6, the information processing device 400 receives input of information about the user (step S601). Here, the information about the user is information on the user's age, urine pH, smoking habit, and degree of obesity. The information processing apparatus 400 may receive direct input from the user via the input unit 420, or receive information via communication from another device such as a user terminal held by the user via the communication unit 410. It may be accepted by Communication unit 410 or input unit 420 transmits the received information about the user to control unit 430 .

Upon receiving the information about the user, the estimating unit 431 of the control unit 430 refers to the disease possibility information 441 based on the user's age, urine pH, smoking habit, and obesity level to determine whether the user is The possibility of developing diabetes 10 years later is estimated (step S602). Then, the estimation unit 431 outputs the estimated estimation result via the output unit 450 (step S604). The output of the estimation result by the output unit 450 may be output as an image or a character string on the monitor of the information processing device 400, or may be output as a voice from the speaker of the information processing device 400, or the communication unit 410. It may also be the output by transfer to another device via the . Also, the estimation unit 431 transmits the estimated result to the proposal unit 432 .

The proposing unit 432 proposes preventive measures for preventing the user from developing diabetes based on the estimation result of the possibility of the user developing diabetes transmitted from the estimating unit 431 (step S604), and ends the process. The proposal unit 432 outputs the proposed preventive measures via the output unit 450 . The proposal by the proposal unit 432 may be output in any form of display of an image or a character string, output by voice, or information transfer from another device, similarly to the output of the estimation result by the estimation unit 431 .

<Summary of Embodiment 2>
According to the information processing apparatus 400 according to the second embodiment, by using the degree of body mass index (BMI), which is conventionally considered to be closely related to diabetes, the user will be diagnosed with diabetes after a predetermined number of years (for example, after 10 years). It is possible to estimate the possibility more accurately than the information processing apparatus 100 of the first embodiment.

<Embodiment 3>
In Embodiments 1 and 2 above, the description is based on the assumption that the user is aware of his/her own urine pH. However, it is not uncommon for normal users to measure their own urine pH. Therefore, in the third embodiment, an estimation system will be described that can measure the urine pH and estimate the possibility that the user will develop diabetes 10 years from now without forcing the user to perform complicated processing.

<Configuration>
<System configuration>
FIG. 7 is a diagram showing a system configuration example of an estimation system for estimating the possibility that a user will develop diabetes.

As shown in FIG. 7, the estimation system 700 comprises an information processing device 800, a measurement device 900, and a user terminal 1000 connected via a network 710 so as to be able to communicate with each other.

The information processing device 800 is a device for estimating the possibility that a user will develop diabetes in the same manner as the information processing devices 100 and 200 shown in the first and second embodiments, and transmits the estimated result to the user terminal 1000 of the user. Send. The measuring device 900 is provided in a toilet bowl, measures the pH of the user's urine, and transmits the result to the information processing device 800 . As described above, in the third embodiment, a mode of using the urine pH measured by the measuring device 900 will be described. The mounting position of the measuring unit 930 of the measuring device 900 to the toilet bowl is not limited to that shown in the figure. For example, when mounting to the toilet bowl, the measuring unit 930 may be attached to the front side of the bowl.

<Configuration of information processing device>
FIG. 8 is a block diagram showing a configuration example of an information processing apparatus 800 according to the third embodiment. As shown in FIG. 8 , the information processing device 800 includes a communication section 810 , an input section 820 , a control section 830 , a storage section 840 and an output section 850 . The control unit 830 also includes an estimation unit 831 and a proposal unit 832 , and the storage unit 840 stores disease possibility information 841 and user information 842 . Each part of the information processing apparatus 800 operates similarly to each part having the same name as the information processing apparatus 100 shown in the first embodiment and the information processing apparatus 400 shown in the second embodiment. Therefore, in the third embodiment, the information processing apparatus 800, like the information processing apparatus 400, determines the possibility that the user will develop diabetes based on the user's age, urine pH, smoking habit, and degree of obesity. Assuming that this is an apparatus for estimation, differences from the second embodiment will be described.

The communication unit 810 receives a user ID as information about the user transmitted from the measuring device 900 and information indicating the urine pH of the user. Then, communication unit 810 transmits the received user ID and information indicating urine pH to control unit 830 .

The control unit 830 includes, as functions of the control unit 830, an estimation unit 831, a proposal unit 832, an acquisition unit 833, and an identification unit 834.

The acquisition unit 833 acquires the user's urine pH measured by the measuring device 900 . The acquisition unit 833 transmits the acquired urine pH to the estimation unit 831 .

The identifying unit 834 refers to the user information 842 based on the user ID received from the measuring device 900 to identify the user whose urine pH is obtained by the obtaining unit 833 . The identifying unit 834 refers to the user information 842 to identify the gender information, the age information, the smoking habit information, and the obesity level information of the user, and transmits the information to the estimating unit 831 .

When the gender information of the user transmitted from the identifying unit 834 indicates that the user is male, the estimating unit 831 calculates the urine pH transmitted from the acquiring unit 833, the age-related information transmitted from the identifying unit 834, and the smoking habit. Using the presence/absence and the degree of obesity, the disease possibility information 841 is referenced to estimate the possibility that the user will develop diabetes 10 years from now.

The disease possibility information 841 is the same as the disease possibility information 441 described in the second embodiment.

The above is the configuration of the information processing apparatus 800 according to the third embodiment.

<Configuration of measuring device>
FIG. 9 is a block diagram showing a configuration example of the measuring device 900. As shown in FIG.

The measuring device 900 is a sensor that is provided in a toilet bowl or the like, measures the user's urine pH, and transmits the measured information to the information processing device 800 .

As shown in FIG. 9, the measurement device 900 includes a communication section 910, an input section 920, a measurement section 930, a control section 940, and a storage section 950. The measuring device 900 may comprise an output section 960 .

A communication unit 910 is a communication interface having a function for executing communication with other devices. The communication unit 910 may perform communication using any communication protocol as long as it can communicate with another device, and may be wired or wireless communication. The communication unit 910 communicates with the information processing device 800 to receive the morbidity possibility information and the proposal information transmitted from the information processing device 800 and transmit them to the control unit 940 .

The input unit 920 is an input interface that receives input of information regarding the user of the user terminal 1000 . For example, the input unit 920 receives information that uniquely identifies the user output by a health monitoring application or the like installed in the user terminal 300 owned by the user (for example, a QR code (registered trademark) including user ID information) ( Information that identifies the user is hereinafter referred to as "user identification information"), or magnetic information including the user's user ID contained in the IC (Integrated Circuit) card owned by the user, WiMAX (Worldwide Interoperability for Microwave Access) , WiFi (Wireless Fidelity) and wireless LAN (Local Area Network) such as Bluetooth (registered trademark). The user ID read from the IC card) is transmitted to the control unit 940 . Also, the input unit 920 may be realized by soft keys such as a touch panel, or may be realized by hard keys. Alternatively, the input unit 920 may be a microphone for receiving voice input. In this case, the input unit 920 may receive the input of the user ID directly from the user and transmit it to the control unit 940 .

The measurement unit 930 is a sensor that is provided in a toilet bowl and has a function of measuring the urine pH of the user's urine based on the urine of the user who used the toilet bowl.

For example, the measurement unit 930 may include an electrode unit for measuring urine pH.

The electrode unit includes two or more electrodes, and the electromotive force (potential difference, voltage value) by the electrolyte and the current value flowing between the electrodes immersed in urination or urination-containing water for a specific component in urine, which is an electrolyte. The above electrodes are used to measure and generate voltage information. Specifically, for example, the electrode unit is composed of two or more electrodes, a potentiometer, and an ammeter to measure the concentration of a specific component in urine. For the electrode unit, for example, among two or more electrodes, one is used as a reference electrode and the other electrode is used as a working electrode. A potentiometer measures the electromotive force difference between the working electrode and the reference electrode in response to the concentration (activity) of the urinary component. The electrode unit generates voltage information based on the measurement results.

Here, "voltage information" may be information related to the electromotive force (potential difference, voltage value) generated by a specific component (electrolyte) in urine generated using two or more electrodes. Although an example using an ion-selective electrode method is shown here, an enzyme electrode method (GOD (Glucose OxiDase)) may be used. may be used. As a result, the concentration of the specific component in urine can be measured based on the generated voltage information.

As an example, the potential difference E as voltage information, the pH value _pHi of the reference electrode, and the pH value _pHo , which is the hydrogen ion concentration as a characteristic component in urine, can be expressed by the following equation (1). . Usually pH _i ≈7, where α designates the sensitivity and e the asymmetry potential. For example, in an ideal electrode with a water temperature of 25° C., α=1 and e=0.

The measurement unit 930 calculates the pH _o specified by the above formula as the urine pH of the user, and transmits it to the control unit 940 .

The control section 940 is a processor having a function of controlling each section of the measuring device 900 . The control unit 940 uses various programs and data stored in the storage unit 950 to implement the functions that the measurement device 900 should perform. Control unit 940 transmits the user ID transmitted from input unit 920 and the urine pH measured by measurement unit 930 to information processing apparatus 800 via communication unit 910 .

The storage unit 950 has a function of storing various programs and data required by the measuring device 900 for its operation. The storage unit 950 can be implemented by, for example, a HDD (Hard Disc Drive), SSD (Solid State Drive), flash memory, or the like.

The output unit 960 has a function of outputting information specified by the control unit 940 . The output unit 960 may be implemented by a monitor, a speaker, or the like provided in the measuring device 900 . For example, when the input unit 920 fails to read the user ID, the output unit 960 may display information prompting the user to read the user ID again. may be displayed.

The above is the configuration example of the measuring device 900 .

<Configuration of user terminal>
FIG. 10 is a block diagram showing a configuration example of the user terminal 1000. As shown in FIG.

The user terminal 1000 may be realized by a smart phone, a mobile phone, a tablet terminal, a PC, a notebook PC, etc., but is not limited to these.

As shown in FIG. 10, the user terminal 1000 includes a communication section 1010, an input section 1020, a control section 1030, a storage section 1040, and an output section 1050.

A communication unit 1010 is a communication interface having a function for executing communication with other devices. The communication unit 1010 may perform communication using any communication protocol as long as it can communicate with another device, and may be wired or wireless communication. The communication unit 1010 communicates with the information processing device 800 to receive the morbidity possibility information and the proposal information transmitted from the information processing device 800 and transmit them to the control unit 1030 .

The input unit 1020 is an input interface having a function of receiving input from the user of the user terminal 1000 and transmitting it to the control unit 1030 . The input unit 1020 may be realized by soft keys such as a touch panel, or may be realized by hard keys. Alternatively, input unit 1020 may be a microphone for receiving voice input. The input unit 1020 transmits input contents input by the user to the control unit 1030 .

The control unit 1030 is a processor having a function of controlling each unit of the user terminal 1000 . The control unit 1030 uses various programs and data stored in the storage unit 1040 to implement the functions that the user terminal 1000 should perform. Based on the morbidity possibility information transmitted from the information processing device 800, the control unit 1030 causes the output unit 1050 to output information indicating the possibility that the user of the user terminal 1000 will develop diabetes in 10 years. Based on the proposal information transmitted from the information processing device 800, the control unit 1030 causes the output unit 1050 to output information indicating preventive measures to prevent the user of the user terminal 1000 from developing diabetes in 10 years.

The storage unit 1040 has a function of storing various programs and data required by the user terminal 1000 for operation. Storage unit 1040 can be implemented by, for example, a HDD (Hard Disc Drive), SSD (Solid State Drive), flash memory, or the like.

The output unit 1050 has a function of outputting information specified by the control unit 1030 . The output unit 1050 may be realized by a monitor, a speaker, or the like provided in the user terminal 1000 or connected to the user terminal 1000 . The output unit 1050 may output a character string or an image, or may output a sound. The output unit 1050 may display information indicating the possibility that the user will develop diabetes in 10 years, or display information indicating preventive measures for preventing the user from developing diabetes.

The above is an example of the configuration of the user terminal 1000.

<Data>
FIG. 11 is a data conceptual diagram showing a data configuration example of user information 842, which is information held by the information processing apparatus 800. As shown in FIG.

As shown in FIG. 11, user information 842 is information in which user ID 1101, name 1102, gender 1103, date of birth 1104, BMI 1105, smoking habit 1106, and address 1107 are associated.

The user ID 1101 is unique identification information for each user that is given to uniquely distinguish each user managed by the information processing apparatus 800 .

The name 1102 is information indicating the name of the user indicated by the corresponding user ID 1101. The gender 1103 is information indicating the gender of the user indicated by the corresponding user ID 1101.

The date of birth 1104 is information indicating the date of birth of the user indicated by the corresponding user ID 1101, and is information for specifying the age of the user.

The BMI 1105 is information indicating the degree of obesity of the user indicated by the corresponding user ID 1101.

The smoking habit 1106 is information indicating whether or not the user indicated by the corresponding user ID 1101 has a smoking habit.

The address 1107 is information on the user terminal held by the user indicated by the corresponding user ID 1101, and is information indicating the destination of the information indicating the possibility of developing diabetes.

In the example of FIG. 11, the name 1102 of the user whose user ID 1101 is "U02338" is "A mountain A child", the gender 1103 is "male", and the date of birth 1104 is "1964 July". Month 6", BMI 1105 is "28.2", Smoking Habit 1106 is "Yes", and Address is "AAA@AA.co.jp". Since this user has a high BMI and a habit of smoking, it is predicted that the possibility of developing diabetes is high.

Note that the user information 842 may include information other than these pieces of information. For example, the urine pH measured by the measuring device 900 may be registered in the user information 842 together with the measurement date. Also, some information may not be included in the user information 842, for example, the name 1102 may not be included in the user information 842. FIG. Also, for example, if each piece of information required by the estimation unit 831 of the information processing device 800 for estimation processing can be acquired, the information does not have to be included in the user information 842 .

<Action>
FIG. 12 is a sequence diagram illustrating an example of exchanges between devices related to the estimation system.

As shown in FIG. 12, the measuring device 900 accepts input of user information (step S1201). The user information that is input here is the information of the user who does the errand. Measuring device 900 measures the user's urine pH (step S1202). Then, measuring device 900 transmits the received user information and the measured urine pH to information processing device 800 (step S1203).

Upon receiving the user information and the urine pH, the information processing apparatus 800 identifies the user based on the user information (step S1204). Then, the specified user estimates the possibility of being affected 10 years later (step S1205). The information processing apparatus 800 transmits morbidity probability information indicating the estimation result and proposal information based on the estimation result to the user terminal 1000 (step S1206).

When the user terminal 1000 receives the morbidity possibility information and the proposal information transmitted from the information processing device 800, the user terminal 1000 displays the contents indicated by the received morbidity possibility information and the contents of the proposal information (step S1207). . As a result, the user can recognize the possibility that he or she will develop diabetes 10 years from now on his/her own terminal, and can recognize what should be done to prevent diabetes.

FIG. 13 is a flow chart showing an operation example of the measuring device 900 for realizing the exchange shown in FIG.

As shown in FIG. 13, the input unit 920 of the measuring device 900 receives input of a user ID from the user (step S1301). Input unit 920 transmits the input user ID to control unit 940 .

Next, the measurement unit 930 of the measurement device receives the user's urine and measures the urine pH of the user's urine (step S1302). Measurement unit 930 then transmits the measured urine pH to control unit 940 .

When the user ID is transmitted from the input unit 920 and the urine pH is transmitted from the measurement unit 930 , the control unit 940 transmits measurement information in which the user ID and the urine pH are associated with each other via the communication unit 910 . Send to the processing device 800 .

As a result, the user can notify the information processing device 800 of his/her own urinary pH without particular effort, and can have his/her own possibility of developing diabetes estimated.

FIG. 14 is a flow chart showing an operation example of the information processing device 800 for realizing the exchange shown in FIG.

The communication unit 810 of the information processing device 800 receives, from the measuring device 900, information in which the user ID as information about the user and the urine pH measured by the measuring device 900 are associated with the user's urine pH. (Step S1401). Communication unit 810 transmits the received user ID and urine pH to control unit 830 .

The specifying unit 834 of the control unit 830 refers to the user information 842 based on the transmitted user ID, specifies the information of the user (step S1402), and transmits it to the estimating unit 831. Here, the user information to be transmitted is information regarding the user's sex, age, degree of obesity, and whether or not he or she has a smoking habit. Also, the acquisition unit 833 acquires the user's urine pH and transmits it to the estimation unit 831 .

The estimation unit 831 determines whether the user is male based on the user's gender information included in the transmitted user information (step S1403). Compared to men, the possibility of developing diabetes in women cannot be determined from age, urinary pH, degree of obesity, and whether or not they have a smoking habit. accuracy is reduced). If the estimation unit 831 determines that the user is not male (NO in step S1403), the process ends without doing anything.

If it is determined that the user is male (YES in step S1403), the estimating unit 831 collects the transmitted urine pH (urine pH measured by the measuring device 900) and the user specified by the specifying unit 834. The disease possibility information 841 is referenced based on the age of the user, the presence or absence of a smoking habit, and the degree of obesity to estimate the possibility of the user suffering from diabetes (step S1404). The estimation unit 831 transmits the estimation result to the proposal unit 832 .

The estimation unit 831 generates morbidity possibility information indicating the estimated possibility that the user will develop diabetes (step S1405). As an example, the estimating unit 831 determines that the estimated index value indicating the possibility that the user will develop diabetes differs from the user who is of the same age as the user and at least one of urine pH, smoking habit, and degree of obesity. The index value for the user and the morbidity probability information are generated.

In addition, based on the estimation result transmitted from the estimation unit 831, the proposal unit 832 generates proposal information indicating proposal content for reducing the possibility of the user suffering from diabetes (step S1406).

The control unit 830 transmits the disease probability information generated by the estimation unit 831 and the proposal information generated by the proposal unit 832 to the user terminal 1000 via the communication unit 810 (step S1407), and ends the process. .

FIG. 15 is a flow chart showing an operation example of the user terminal 1000 for realizing the exchange shown in FIG.

As shown in FIG. 15, the communication unit 1010 of the user terminal 1000 receives the disease probability information and the proposal information transmitted from the information processing device 800 (step S1501). The communication unit 1010 transmits the received morbidity possibility information and proposal information to the control unit 1030 .

When the control unit 1030 receives the morbidity possibility information from the communication unit 1010, the control unit 1030 outputs to the output unit 850 information indicating the possibility that the user of the user terminal 1000 will develop diabetes in 10 years, which is indicated in the received morbidity possibility information. Output (display) (step S1502).

Further, when the proposal information is received from the communication unit 1010, the control unit 1030 displays preventive measures for the user indicated in the received proposal information to prevent diabetes (step S1503), and ends the process. .

<Display example>
FIG. 16A is a diagram showing a display example of the estimation result on the user terminal 1000. FIG. FIG. 16(b) is a diagram showing a display example of proposal information on the user terminal 1000. As shown in FIG. Note that although the example of the display by the user terminal 1000 is used here, the display on the monitor of the information processing device 800 (100, 400) may be the same.

As shown in FIG. 16(a), the user terminal 1000 displays information 1601 indicating the possibility of the user suffering from diabetes. As illustrated, the information 1601 indicating the likelihood that the user will develop diabetes is comparison information with other users, that is, how high the likelihood that the user will develop diabetes is compared to other users. It becomes information indicating By displaying information that compares the user to other users of the same age, the user can see how likely they are to develop diabetes rather than simply displaying information such as a percentage indicating the likelihood of developing diabetes. easy to feel. Note that the percentages shown in FIG. 16(a) are index values indicating the possibility of the user's own diabetes, and other classifications (different urine pH classifications, different BMI classifications, smoking habits, non-smoking habits, etc.). ) can be calculated from the index value of

In addition, as shown in FIG. 16B, the user terminal 1000 includes information 1601 indicating the possibility that the user will develop diabetes, as well as proposal information indicating preventive measures for reducing the possibility that the user will develop diabetes. 1602 may be displayed. FIG. 16B shows an example in which information 1601 indicating the possibility of developing diabetes and proposal information 1602 are displayed in parallel, but proposal information 1602 may be displayed alone.
<Summary of Embodiment 3>

According to the information processing apparatus 800 according to the third embodiment, it is possible to estimate the possibility of the user suffering from diabetes without directly accepting input of information about the user from the user. Since the user can recognize the possibility that he/she will be diagnosed with diabetes just by doing errands, it is possible to provide the estimation system and the information processing apparatus 800 that are highly convenient for the user.

<Supplement>
The configurations shown in the above embodiments are examples, and are not limited to the above embodiments.

In the third embodiment, the information processing apparatus 800 may be configured to exclude from the estimation by the estimation unit 831 if the target user is already suffering from diabetes. This is because it is meaningless to estimate the possibility of developing diabetes when the subject already has diabetes. Whether or not the user has diabetes is determined by, for example, storing information indicating whether or not the user has diabetes as information registered in the user information 842, and using the information. good. That is, before estimating the possibility that the user will have diabetes 10 years from now, the estimation unit 831 refers to the user information 842 to confirm that the user does not have diabetes, and then executes the estimation. It is good to do. The same applies to the information processing apparatuses 100 and 400 as well.

The information processing device (100, 400, 800) according to the present invention may be used as part of telemedicine in conjunction with a medical institution or the like. For example, the user information 842 stored in the storage unit 840 stores information on the medical institution, doctor, etc. associated with each user, and when updating the measurement/test result DB, etc., the measured values and test result data of the DB are stored. The information processing apparatus 800 is configured so that the information is transmitted to the medical institution or the like, and the doctor or the like can remotely examine the patient's health based on the transmitted data and provide guidance, etc. even if the patient is at home. good too. Further, the user information included in the user information 842 may be obtained from a server of a medical institution or the like, or may be obtained from an electronic medical chart or the like with the permission of a doctor or the like.

Further, each functional unit of the information processing apparatuses 100, 400, 800, the measuring apparatus 900, and the user terminal 1000 includes a logic circuit (hardware) formed in an integrated circuit (IC (Integrated Circuit) chip, LSI (Large Scale Integration)) or the like. It may be implemented by a dedicated circuit, or by software using a CPU (Central Processing Unit) and memory. Further, each functional unit may be implemented by one or more integrated circuits, and the functions of multiple functional units may be implemented by one integrated circuit. LSIs are sometimes called VLSIs, super LSIs, ultra LSIs, etc., depending on the degree of integration. It should be noted that the term "circuit" here may also include the meaning of digital processing by a computer, that is, functional processing by software. Also, the circuit may be realized by a reconfigurable circuit (for example, FPGA: Field ProgrammableGateAway).

When the functional units of the information processing devices 100, 400, 800, the measuring device 900, and the user terminal 1000 are realized by software, the functional units of the information processing devices 100, 400, 800, the measuring device 900, and the user terminal 1000 are each A CPU that executes the instructions of the estimation program, which is software that realizes the function, a ROM (Read Only Memory) or storage device in which the estimation program and various data are recorded so that the computer (or CPU) can read them (these are referred to as "recording media") ), a RAM (Random Access Memory) for developing the estimation program, and the like. The object of the present invention is achieved by a computer (or CPU) reading and executing the estimation program from the recording medium. As the recording medium, a "non-temporary tangible medium" such as a tape, disk, card, semiconductor memory, programmable logic circuit, or the like can be used. Also, the estimation program may be supplied to the computer via any transmission medium (communication network, broadcast wave, etc.) capable of transmitting the estimation program. The invention can also be implemented in the form of a data signal embedded in a carrier wave, in which the estimation program is embodied by electronic transmission.

The estimation program can be implemented using, for example, script languages such as ActionScript and JavaScript (registered trademark), object-oriented programming languages such as Objective-C and Java (registered trademark), markup languages such as HTML5, and the like.

100, 400, 800 information processors 110, 410, 810, 910, 1010 communication units 120, 420, 820, 920, 1020 input units 130, 430, 830, 940, 1030 control units 131, 431, 831 estimation unit 132, 432, 832 proposal units 140, 440, 840, 950, 1040 storage units 150, 450, 850, 960, 1050 output unit 900 measurement device 930 measurement unit 1000 user terminal

Claims (12)

a reception unit that receives input of the user's age, the presence or absence of a smoking habit, and urine pH as user information about the user;
an estimation unit that estimates the possibility that the user will develop diabetes based on the user information;
a storage unit for storing, for each predetermined range of the urine pH, disease possibility information indicating the possibility of contracting diabetes depending on the presence or absence of a smoking habit;
an output unit that outputs information indicating the possibility that the user will suffer from diabetes estimated by the estimation unit;
Information processing apparatus, wherein the estimation unit estimates a possibility that the user will develop diabetes based on the user information and the disease possibility information. The storage unit stores the disease possibility information for each user's age within a predetermined range,
2. The estimating unit estimates the possibility that the user will develop diabetes based on the presence or absence of a smoking habit for each predetermined range of the urine pH according to the age of the user. The information processing device according to . The user information further includes the user's degree of obesity,
The disease possibility information is information indicating the possibility of contracting diabetes according to the magnitude of the degree of obesity with respect to a predetermined threshold value for each predetermined range of the urine pH,
The estimating unit estimates the possibility that the user will develop diabetes according to the obesity level relative to a predetermined threshold value and whether or not the user has a smoking habit, for each predetermined range of the urine pH. Item 3. The information processing device according to Item 1 or 2. The estimating unit compares with other users of the same age as the user, whose obesity degree is less than the predetermined threshold, and who has no smoking habit, and compares the possibility that the user will suffer from diabetes. 4. The information processing apparatus according to any one of claims 1 to 3, characterized in that the multiplier that indicates the likelihood of the user being diagnosed with diabetes is estimated. The information processing apparatus according to any one of claims 1 to 4, wherein the estimation unit estimates the possibility that the user will develop diabetes after a predetermined number of years. 6. The method according to any one of claims 1 to 5, further comprising: a proposal unit that makes a proposal to prevent the user from developing diabetes based on the possibility that the user will develop diabetes estimated by the estimation unit. The information processing device according to item 1. A communication unit that is attached to the toilet bowl and communicates with a measuring device that measures pH,
The information processing apparatus according to any one of claims 1 to 6, wherein the reception unit receives, as the urine pH of the user, the pH measured by the measurement device and received by the communication unit. . The communication unit receives specific information that identifies a user corresponding to the urine pH measured by the measuring device,
The information processing apparatus according to claim 7, wherein the output unit transmits information indicating the possibility of contracting diabetes to a terminal of the user indicated by the specific information. The information processing apparatus according to any one of claims 1 to 8, wherein the user is male. The reception unit further receives disease information indicating that the user has diabetes,
The information processing device is
10. The method according to any one of claims 1 to 9, further comprising an updating unit that updates the disease possibility information based on the disease information and user information of a user corresponding to the disease information. information processing equipment. A computer-assisted estimation method for estimating the likelihood that a user will develop diabetes,
a receiving step of receiving input of the user's age, the presence or absence of a smoking habit, and urine pH as user information about the user;
an estimation step of estimating the possibility that the user will develop diabetes based on the user information;
an output step of outputting information indicating the possibility that the user will suffer from diabetes estimated by the estimation step;
In the estimating step, for each predetermined range of the urine pH, the user information and the disease stored in a storage unit that stores disease possibility information indicating a possibility of developing diabetes according to the presence or absence of a smoking habit. An estimation method for estimating the possibility that the user will develop diabetes based on possibility information. to the computer,
a reception function that receives input of the user's age, the presence or absence of a smoking habit, and urine pH as user information about the user;
an estimation function for estimating the possibility that the user will develop diabetes based on the user information;
an output function for outputting information indicating the possibility that the user will develop diabetes estimated by the estimation function;
The estimating function includes the user information and the disease stored in the storage unit that stores disease possibility information indicating the possibility of contracting diabetes according to the presence or absence of a smoking habit for each predetermined range of the urine pH. an estimation program for estimating the likelihood that the user will develop diabetes based on the likelihood information.

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