WO2022244265A1 - Examination guide service server and examination guide method - Google Patents

Abstract

Provided are an examination guide service server and an examination guide method such that it is possible to receive advice necessary to suitably receive a clinical examination or an examination accompanying medical practice, such as an endoscopy. Examination risk when an examinee receives an endoscopy is evaluated according to information from an examinee terminal (S11), and on the basis of this evaluation result of the examination risk, chronological advice is generated for the interval until the endoscopy, and this chronological advice is transmitted to the examinee terminal (S13). The examination risk is at least one among a cleansing risk and a polyp risk.

Description

Inspection guide service server and inspection guide method

The present invention provides an examination guide service server capable of providing an appropriate guide to a subject who undergoes an examination involving medical procedures such as an endoscopy or a clinical examination before the actual examination. It relates to an inspection guide method.

　Medical facilities are equipped with multiple inspection devices, and appropriate endoscopes are prepared according to the inspection items of patients and subjects, and these endoscopes are used for inspection. In this case, it is necessary to set a schedule for using the endoscope in good condition, taking into consideration the cleaning state of the endoscope and the like, as well as the consumption state and aging state. Therefore, in Patent Literature 1, an endoscopy work support system is proposed that appropriately schedules endoscopy work.

JP 2017-113082 A

The endoscopy work support system of Patent Document 1 described above describes a technique for appropriately scheduling endoscopy work within a medical facility. However, there is no mention of support such as advice for receiving appropriate examinations. In actual medical practice, there are various things that must be done before the subject visits the hospital, such as taking a laxative and washing the intestines before the subject arrives. Therefore, by controlling including these, it becomes possible to receive an appropriate examination. If there is advice on taking treatment drugs before the examination and physical condition management before coming to the hospital, the examinee can take the examination with peace of mind.

The present invention has been made in view of such circumstances, and an examination guide service server capable of receiving necessary advice for appropriately undergoing examinations involving medical procedures such as endoscopy and clinical examinations. and to provide an inspection guide method.

In order to achieve the above object, an examination guide service server according to a first aspect of the present invention includes a risk determination unit that determines an examination risk when a subject undergoes an endoscopy according to information from a subject terminal; An advice creation unit that creates chronological advice before the endoscopy based on the determination result of examination risk, and a transmission unit that transmits the chronological advice to the subject terminal. .

In the examination guide service server according to a second invention, in the first invention, the chronological advice switches between a plurality of pieces of advice according to the target schedule and the examination risk.
An examination guide service server according to a third invention is the examination guide service server according to the first invention, wherein the chronological advice determines an effect of the chronological advice according to the improvement of the examination risk, and switches between a plurality of pieces of advice.

An inspection guide service server according to a fourth aspect of the present invention is the risk of creating improvement advice for improving the inspection risk when the risk determination unit determines that the inspection risk is high when the inspection is performed in the first aspect of the invention. A reduction proposal section is provided, and the improvement advice is included when the advice section prepares the chronological advice.
An examination guide apparatus according to a fifth aspect of the present invention is the examination guide apparatus according to the fourth aspect, further comprising a schedule proposing unit that proposes an examination schedule, and the schedule proposing unit, in a state in which the examination risk of the subject is reduced, Create different advice than before the inspection risk was reduced.

According to a sixth aspect of the present invention, there is provided an examination guide apparatus according to the fifth aspect, wherein the schedule proposing section proposes the time when the examination risk is reduced as the endoscopy examination time.
In the examination guide apparatus according to a seventh invention, in the fifth invention, the schedule proposal unit can selectively propose a plurality of candidates as the timing when the examination risk is reduced according to the situation of the examination facility. is.

An examination guide apparatus according to an eighth invention is the examination guide apparatus according to the first invention, wherein the risk determination unit determines the examination risk based on information on the subject's profile and lifestyle habits.
A ninth aspect of the present invention provides an examination guide apparatus according to the first aspect, wherein the examination risk is a risk of increased variation in time from preparation to completion of the endoscopic examination.
A tenth aspect of the present invention provides an inspection guide apparatus according to the first aspect, wherein the inspection risk is at least one of a cleaning risk and a polyprick risk.

An examination guide method according to an eleventh aspect of the present invention determines whether or not there is an examination risk when a subject undergoes a clinical examination according to information from a subject terminal, and based on the examination risk determination result, A chronological advice is created before the examination, and the chronological advice is transmitted to the subject terminal.
A mobile terminal according to a twelfth invention comprises a user information acquisition unit for acquiring profile information and lifestyle information of a mobile terminal user, and the lifestyle information to reduce restrictions that occur when undergoing a specific clinical examination in the future. and a display unit for displaying the correction points determined by the determination unit.
A mobile terminal control method according to a thirteenth aspect of the present invention obtains profile information and lifestyle information of a mobile terminal user, and uses the lifestyle information to reduce restrictions that occur when undergoing a specific clinical examination in the future. It is possible to determine points to be corrected in lifestyle habits by using the personal computer, and to transmit the determined points to be corrected.

According to the present invention, it is possible to provide an examination guide service server and an examination guide method that enable users to receive necessary advice for appropriately undergoing examinations involving medical procedures such as endoscopic examinations and clinical examinations.

1 is a block diagram showing the configuration of an endoscopy support system according to a first embodiment of the present invention; FIG. 4 is a flow chart showing operations in the service server of the endoscopy support system according to the first embodiment of the present invention; 4 is a flowchart showing operation of displaying an examination time guide in the service server of the endoscopy support system according to the first embodiment of the present invention; FIG. 5 is a block diagram showing the configuration of an endoscopy support system according to a second embodiment of the present invention; FIG. 9 is a flow chart showing operations in the service server of the endoscopy support system according to the second embodiment of the present invention; FIG. 10 is a flow chart showing the operation of displaying an examination time guide in the service server of the endoscopy support system according to the second embodiment of the present invention; 4 is a flow chart showing the operation of constipation prediction AI in the endoscopy support system according to the first and second embodiments of the present invention; 4 is a flowchart showing the operation of polyp prediction AI in the endoscopy support system according to the first and second embodiments of the present invention, and a guide display on the user terminal. 4 is a flowchart showing the operation of constipation improvement time prediction AI in the endoscopy support system according to the first and second embodiments of the present invention; FIG. 4 is a diagram showing an example of a subject's situation when predicting the time to improve constipation using the endoscopy support system according to the first and second embodiments of the present invention; FIG. 4 is a chart showing a determination method for determining constipation risk using the endoscopy support system according to the first and second embodiments of the present invention; FIG. FIG. 5 is a diagram showing scores in consideration of age when constipation risk is determined using the endoscopy support system according to the first and second embodiments of the present invention; FIG. 5 is a diagram showing scores in consideration of the average number of steps per day when determining the risk of constipation using the endoscopy support system according to the first and second embodiments of the present invention; FIG. 5 is a diagram showing scores in consideration of water intake when judging the risk of constipation using the endoscopy support system according to the first and second embodiments of the present invention; FIG. 4 is a diagram showing scores in consideration of sleep hours when determining constipation risk using the endoscopy support system according to the first and second embodiments of the present invention; FIG. 5 is a diagram showing scores in consideration of pulse rate (stress) when judging the risk of constipation using the endoscopy support system according to the first and second embodiments of the present invention; FIG. 4 is a chart showing a determination method for determining polyprisk using the endoscopy support system according to the first and second embodiments of the present invention; FIG. 4 is a graph showing the relationship between BMI and polyprisk when determining polyprisk using the endoscopy support system according to the first and second embodiments of the present invention.

Below, as an embodiment of the present invention, an example in which the present invention is applied to an endoscopy support system in which preparations before an examination and medical actions during an examination can be performed will be described. In colonoscopy, in order to examine the large intestine, the patient takes an intestinal cleansing agent to clean the large intestine before undergoing the examination. Of course, the present invention is not limited to endoscopy, and can be applied to other clinical examinations and examinations that involve medical practice. First, an endoscopy support system according to the first embodiment will be described with reference to FIGS. 1 to 3. FIG. FIG. 1 is a block diagram showing the overall configuration of an endoscopy support system according to the first embodiment. This endoscopy support system comprises a service server 10 , a user terminal 20 , and in- hospital systems 30 and 35 .

The service server 10 can be connected to a user terminal 20 used by users through a communication network such as the Internet, and hospital systems 30 and 35 used by medical staff in medical facilities, and provides various services to users. can provide. The service server 10 has a processing device such as a CPU (Central Processing Unit), a memory that stores programs, and other peripheral circuits. , a risk reduction proposal unit 15 , a hospital policy confirmation unit 16 , a time prediction unit 17 , and an examination result recording unit 18 . The schedule management unit 13, the constipation/polyposis risk determination unit 14, the risk reduction proposal unit 15, the hospital policy confirmation unit 16, and the time prediction unit 17 may be realized by hardware circuits or the like. It may be realized by a processor executing a program stored in a memory.

The control unit 11 controls the service server 10 as a whole. The control unit 11 is composed of one or a plurality of processors having a processing device such as a CPU and a memory storing a program, etc., and can control each unit in the service server 10 by executing the program.

The communication unit 12 has a communication circuit (including a transmission circuit and a reception circuit) provided in the peripheral circuit, and can communicate with each communication unit in the user terminal 20 and the hospital systems 30 and 35 . As communication, for example, when the risk reduction proposal unit 15 creates improvement advice, the improvement advice is transmitted to the user terminal 20 . The communication unit 12 functions as a transmission unit that transmits chronological advice to the subject terminal (for example, see S13 in FIG. 2).

The schedule management unit 13 manages various times until the examination date when the user (examinee) undergoes the endoscopy. For example, management of timing for the user to take the test (see S9 in FIG. 2), and management from booking the test to actually taking the test (for example, S15 in FIG. 2, see FIG. 3). conduct. In addition, when the improvement advice proposed by the risk reduction proposal unit 15 reduces the examination risk (constipation risk or polyprick risk), the schedule management unit 13 proposes an examination date according to the timing of the reduction. (See S15 in FIG. 2). For example, with regard to endoscopic examination, the schedule management unit 13 adjusts the schedule, including the time from preparation to completion of the examination, the free time of hospitals and examination institutions, and the like. For users who are concerned about the time and effort required for the examination, the time from preparation to completion of the endoscopic examination may be, for example, the time from the time of reservation until discharge from the hospital after treatment. In addition, it may be the time from the start of dietary restrictions or intestinal cleansing to the end of the day's examination and leaving the hospital. In addition to this, for example, there are situations in which stool does not come out easily during a stool test, and there are cases in which it is difficult to adjust the schedule to meet conditions such as fasting in blood tests. The schedule management unit 13 according to this embodiment can also be applied to schedule management of these examinations.

In this way, schedule management from booking to functioning makes it possible to give advice from an early stage before the examination, and it is possible to manage and adjust the physical condition until the examination without overdoing it. Also, if it is the timing of the reservation, contractual procedures will be done there, so at the same time, the details of the advice, the details of the timing, the period of advice (may be up to next year's regular inspection), etc. There is an advantage that the procedures for selection can be completed at the same time. However, this course selection procedure may be performed several days before the actual examination, even if it is not the timing of the reservation, if it is not related to physical condition adjustment that takes a long time.

The schedule management unit 13 functions as a schedule proposal unit that proposes an examination schedule (see S15 in FIG. 2, for example). This schedule proposing section has a function of proposing an appropriate schedule when the subject undergoes examination. There is a fixed timing for health examinations, etc. At this timing, the examination is recommended, and the subject may decide to undergo the examination after worrying about it, which often causes the subject to feel stress. Therefore, in consideration of the situation of the subject, the schedule proposal unit creates advice different from that before the examination risk is reduced in the state where the examination risk of the subject is reduced (for example, see S15 in FIG. 2). ). The schedule proposal unit proposes the time when the examination risk (here, "risk" can be written as examination time risk, assuming that it takes time) is reduced as the time for endoscopic examination (for example, Fig. 2 (see S15 of ). In addition, the schedule proposal unit can selectively propose a plurality of candidates as the timing when the examination risk is reduced according to the situation of the examination facility. The convenient time for the subject may change depending on the situation, and the reservation status of the medical facility side may also change depending on the time, and multiple facilities may be candidates. Therefore, the schedule management unit 13 takes these factors into consideration and enables selection of a plurality of candidates that match the subject and the medical facility side.

The constipation/polyp risk determination unit 14 determines test risks such as constipation and polyps when the user (subject) undergoes the test. When undergoing an endoscopy of the large intestine or the like, it is necessary to take a laxative before the examination to cleanse the inside of the intestine, which may take longer than usual due to constipation depending on the examinee. In addition, if a polyp is found during an examination, treatment of the polyp will take time, and the examination time may be lengthened (examination risk, examination time risk). If such risks are known in advance, various measures can be taken. Therefore, the constipation/polyp risk determination unit 14 determines the possibility that the subject is constipated and the possibility that a polyp is found. An inference engine may be provided in the constipation/polyprick risk determination unit 14 to generate an inference model, or inference may be performed using the generated inference model.

The constipation/polyposis risk determination unit 14 determines whether there is an examination risk when the subject undergoes an endoscopy according to information from the subject terminal (or expressed as a risk time determination unit). (see, for example, S7 and S11 in FIG. 2). The risk determination unit determines test risks based on the subject's profile and lifestyle information (see, for example, S3 to S7 in FIG. 2). Examination risk is the risk of high fluctuations in the time from preparation to completion of an endoscopy. Here, from preparation to completion includes appointment for examination, change of diet before examination, preparation for intestinal tract cleansing before examination, transportation to hospital (including the risk of time fluctuation due to going to the toilet during transportation). , congestion status of the hospital, usage status of the endoscopy room in the hospital, variation in examination time of another examinee before the examinee undergoes the examination, time to hear the results after the examination, after the examination Recovery time (when sedatives are used, treatment is performed, etc.), hospital accounting, etc., from when the subject takes action to undergo the test until the test is completed and the patient leaves the hospital Including between. When undergoing an endoscopic examination, it was often difficult for the examinee to predict the end time. becomes possible. The laboratory risk is at least one of a cleaning risk and a polyprisk.

When the constipation/polyp risk determination unit 14 determines that there is a risk of constipation or a risk of polyps, the risk reduction proposal unit 15 reduces these risks (examination time is required due to these factors, and smooth examinations cannot be performed). risk, etc.) is output (for example, see S13 in FIG. 2). It is preferable that this advice is timely from when the subject first receives advice and starts improving his or her lifestyle and eating habits until the day of the actual examination.

The risk reduction proposal unit 15 functions as an advice creation unit that creates chronological advice up to the endoscopy based on the examination risk determination result (see S13 in FIG. 2). The risk reduction proposal unit 15 further functions as a risk reduction proposal unit that creates improvement advice for improving the inspection risk when the risk determination unit determines that the inspection risk is higher than a predetermined value when undergoing inspection (for example, , S13 in FIG. 2). Inspection risks may be quantified as shown in FIGS. 12A to 12E, etc., and improvement advice may be provided when this numerical value is higher than a predetermined value. Improvement advice is included when the advice unit creates chronological advice (see, for example, S13 in FIG. 2).

The hospital policy confirmation unit 16 confirms the hospital policy. When a subject undergoes an endoscopy at a hospital, the policies of each medical facility are not always the same. For example, the start and end times of examinations, laxatives to be used, treatment policies when polyps are found, and the like may differ among medical facilities. Therefore, the hospital policy confirmation unit 16 confirms the policy of each medical facility and records this policy. In confirming this policy, the hospital policy confirmation unit 16 may communicate with the hospital systems 30 and 35 through the communication unit 12 to acquire the policy of each medical facility. Moreover, you may acquire the matter posted on the homepage|website of each medical facility through the internet. If the policy of the medical facility cannot be obtained by this method, it may be entered manually. In addition, according to specific rules, equipment, anesthesia, laxatives, treatments, consultation hours, doctors' profiles, skills, ideas, and other items may be compiled into a database, and policies and the like may be incorporated therein.

The time prediction unit 17 predicts the time required for the subject to undergo the examination. For example, it predicts the time from taking a laxative to cleanse the intestines to the next taking of the laxative, and also predicts when an examination will be possible. If the subject has a risk of constipation, it is predicted that it will take longer than usual (see S15 in FIG. 2). In this case, it predicts when the risk of constipation will be reduced and it will be appropriate to undergo testing. Also, prediction at this time will be described later with reference to FIG. 9 .

The test result recording unit 18 includes an electrically rewritable non-volatile memory, and records the test results in the recording unit when the subject completes an examination such as an endoscopy at the hospital.

The in-hospital system 30 and the in-hospital system 35 are provided in the same hospital in this embodiment, and a plurality of in-hospital systems are similarly provided in other hospitals. One of the in- hospital systems 30 and 35 provided in the same hospital is connected to mobile terminals and PCs (personal computers) used by doctors, nurses, etc., and is used to exchange various information. , and the other is a system for exchanging various information by connecting to mobile terminals and PCs used by workers in administrative departments, dispensing departments, and the like. If there are three or more systems in the same hospital, of course, three or more in-hospital systems may be provided, or they may be integrated into one system. In addition, in the hospital system, there is a device for inputting hospital management policies and specialties, consultation hours, room configuration, devices and equipment owned, skills and profiles of doctors, nurses, and medical staff. It has a device that organizes and records, and the control unit organizes and records the input results.

The schedule, etc. is also managed by the hospital system. Patients and visitors to the hospital are managed and recorded at the counter, by telephone, by e-mail, etc., which room or device is reserved at what time, and which doctor or medical staff is in charge. By providing such a mechanism, it is possible to obtain information on which hospitals and inspection institutions can accept patients at what timing. For example, in the case of an endoscopy, it is necessary to fast and empty the intestines before the examination. is not immediately available for inspection. For this reason, it is necessary to match with the convenience of the examination facility on the day after the day when the decision was made. However, since it is difficult to manage one's physical condition by just thinking about the examination until the day of the examination several days ahead, a guide such as the present embodiment is effective. In addition, in this embodiment, a database in which what kind of examination requires what kind of preparation and pretreatment, precautions before and after the examination, etc., together with time information until the examination date, etc. is recorded. I'm assuming you have it ready. Of course, it is sufficient if this database can refer to something outside the system and present it to the user.

The controllers 31 and 36 in the hospital systems 30 and 35 control the whole in each hospital system 30 and 35. The control units 31 and 36 have a processing device such as a CPU, a memory storing a program, etc., and can execute the program to control each unit in each hospital system. Further, the control units 31 and 36 may operate in cooperation with the hospital systems 30 and 35 in the same hospital.

The schedule management units 32 and 37 manage the schedules of mobile terminal and PC users (doctors, nurses, pharmacists, laboratory technicians, clerks, etc.) in their respective hospital systems. This schedule management is performed in cooperation with the schedule management unit 13 in the service server 10 in conjunction with the subject's examination schedule (including before examination, at the time of examination, and after examination). Through this interlocking, the examinee is provided with guide information such as the recommended timing and time period for visiting the hospital, and advice on precautions and preparation items associated with the examination, in accordance with the timing of openings in the hospital work schedule. It is also possible to adjust the schedule to do so.

The communication units 33 and 38 have communication circuits (including transmission circuits and reception circuits) provided in the peripheral circuits, and communicate with the service server 10 and other communication units in the hospital systems 30 and 35. be able to.

The user terminal 20 may be a PC used by the subject, but in the present embodiment, it will be described assuming a mobile terminal such as a smart phone. In the case of a portable terminal, it is easy for the subject to collect information about lifestyle habits because the subject carries the terminal. A control unit 21 , a communication unit 22 , a clock unit 23 , a lifestyle acquisition unit 24 , and a UI (User Interface) unit 25 are provided in the user terminal 20 . Note that the clock unit 23 and the lifestyle acquisition unit 24 may be realized by a hardware circuit or the like, or may be realized by the control unit 21 executing a program stored in the memory.

The control unit 21 controls the user terminal 20 as a whole. The control unit 21 is composed of one or a plurality of processors having a processing device such as a CPU, a memory storing programs, etc., and can execute programs and control each unit in the user terminal 20 . Further, the constipation risk and polyprisk risk are determined by the constipation/polyprisk determination unit 14 in the service server 10, but an inference engine is provided in the control unit 21 to perform inference about the constipation risk and polyprisk risk. You can do it. The control unit 21 functions as a determination unit that determines correction points of lifestyle habits based on lifestyle habit information in order to reduce restrictions that occur when undergoing a specific clinical examination in the future (see, for example, S11 in FIG. 2). . In other words, if the subject has an examination risk such as constipation risk or polyprick risk, restrictions such as a time-consuming examination will occur. Therefore, the above restrictions can be reduced by correcting lifestyle habits such as eating habits that eliminate constipation. The determination of correction points may be performed by the control unit 21 alone, or may be performed in cooperation with each unit such as the control unit 21 and the risk reduction proposal unit 15 in the service server 10 .

The communication unit 22 has a communication circuit (including a transmission circuit and a reception circuit) provided within the peripheral circuit, and can communicate with the communication unit within the service server 10 . Various information such as schedule management, constipation/polyprisk determination, risk reduction advice, and time prediction can be exchanged with the service server 10 through the communication unit 22 . In addition, the user terminal 22 stores a user's profile, and the lifestyle acquisition unit 24 acquires the user's lifestyle information, and the communication unit 22 can transmit this information to the outside. It is possible. Therefore, the communication unit 22 functions as an information transmission unit that transmits at least one of the mobile terminal user's profile information and lifestyle information. The clock unit 23 has a calendar function and a clock function, and can output current date and time information.

The lifestyle acquisition unit 24 acquires the lifestyle of the subject using the user terminal 20 . For example, by using a positioning system such as GPS (Global Positioning System) in the user terminal 20, a motion sensor, etc., it is possible to know the position and behavior of the user. For example, it is possible to acquire various lifestyle habits such as jogging, going to the gym and exercising, dining out, little movement in the office, going to bed at home, and the like. In addition, when the user terminal 20 has an imaging unit, it is possible to acquire various lifestyle habits such as complexion, meal content, etc. by analyzing the image acquired by the imaging unit. Also, lifestyle habits may be acquired based on information posted on SNS or the like by the user. In addition to the automatic acquisition, lifestyle habits may be acquired through a questionnaire to the user, or the user may directly input their daily behavior and the like into the user terminal 20 through the UI unit 25. Good (see, for example, S1 in FIG. 2). A lifestyle is determined based on the data acquired by the lifestyle acquisition unit 24 (see S5 in FIG. 2). The lifestyle acquisition unit 24 functions as a user information acquisition unit that acquires the mobile terminal user's profile information and lifestyle information (for example, see S1 to S5 in FIG. 2).

The UI unit 25 is an interface for inputting information to the user terminal 20 and outputting information. The UI unit 25 includes a visual (including auditory, etc.) display unit for transmitting information to the subject, and an input unit (for example, a text input unit) for the subject to input information to the user terminal 20. (including voice input section, etc.). The UI unit 25 functions as a display unit that displays correction points determined by the determination unit. In the present embodiment, the service server 10 creates improvement advice and transmits it to the user terminal 20 through the communication section 12 , so the improvement advice (above-mentioned correction points) is displayed on the UI section 25 . In addition, advice such as improvement advice is not limited to visual display, and may be transmitted to the subject. The UI unit 25 functions as a transmission unit that transmits correction points determined by the determination unit. Note that the improvement advice may be created by the control unit 21 or the like in the user terminal 20 .

By constructing such an endoscopic examination support system, the user (examinee) can undergo an endoscopic examination with peace of mind. For example, when an endoscopy is found to require a full day, the subject may find it difficult to leave the entire day open. In such a case, the subject can easily undergo the examination by using the "Leave it to me assistance application" (examination assistance application shown in FIG. 2 to be described later) installed in the user terminal 20. . By using this app you can also get the advice you need to get tested.

In addition, as will be described later, if the subject has a washing risk due to constipation or the like (see S7 in FIG. 2), the washing risk due to constipation or the like created by the risk reduction proposal unit 15 in the service server 10 is reduced. Advice is given to do so (see, for example, S13 in FIG. 2). Furthermore, by executing the improvement advice, it is also possible to display the time when the examination will be performed (this prediction is made by the time prediction unit 17 in the service server 10) (for example, FIG. 2). (see S15 of ). That is, the service server 10 determines the cleaning risk, provides improvement advice according to the determined risk, and after the subject executes the improvement advice, determines the cleaning risk again, and makes improvements according to the most recent cleaning risk. Advice is given. Therefore, in this embodiment, improvement advice is provided over time. In addition, in the present embodiment, an endoscopy can be reserved according to the examination timing (for example, see S19 in FIG. 2).

Next, the operation of the inspection assistance application software will be described using the flowchart shown in FIG. The control unit 11 in the service server 10 cooperates with the control unit 21 in the user terminal 20, controls each unit in the service server 10, and further cooperates with the hospital systems 20 and 35. realized by

When the operation of the inspection assistance application shown in FIG. 2 starts, first, a questionnaire is displayed and input is determined (S1). Here, the control unit 11 causes the UI unit 25 of the user terminal 20 through the communication unit 12 to display a screen for inputting the subject information and the subject's health condition required for examination. display. For example, for determining the risk of constipation, the tendency of defecation, the amount of meals, the regularity of life, the amount of exercise, etc. may be input. When the subject inputs questionnaire items on this screen, the control unit 21 transmits the input items to the service server 10, the service server 10 judges the received contents, and records the judgment items in the recording unit. The questionnaire may include the subject's name, sex, age, medical history, past examination history, and the like.

In addition, information for undergoing an endoscopy may be included as input items in the questionnaire. For example, whether or not the subject drives home on the examination day may be included. It is recommended not to drive home if a sedative was used during the examination. Alternatively, a desired return home time may be input. In this case, the schedule should be managed so that the examination is completed by the desired return home time. In addition, since some subjects are free in the afternoon, it may be possible to fill in a desired time slot for examination, such as requesting this time slot. In this case, the schedule may be managed as desired. The items entered in this step are matched in steps S15 and S19.

In addition, the questionnaire may be input by the user as described above, or the results of past medical interviews may be obtained from the server. When acquiring from a server, from the viewpoint of personal information protection, it is preferable to obtain the user's consent in advance, or to request the user's consent immediately before.

Next, determine the profile (S3). Here, the control unit 11 determines the subject's profile based on the questionnaire results in step S<b>1 and the user's profile information recorded in the recording unit in the user terminal 20 . For this reason, the control unit 11 should be able to receive profile information from the user terminal 20 . The profile includes basic information such as the subject's name, sex, and age, and may also include medical-related information such as past diseases and results of past medical interviews.

Next, determine your lifestyle habits (S5). Here, the control unit 11 determines the lifestyle habits of the user of the user terminal 20 . This determination is made by the control unit 21 based on the user's lifestyle information collected by the lifestyle acquisition unit 24 in the user terminal 20 . The lifestyle habit acquisition unit 24 collects, for example, items tweeted by the user on the SNS, such as "I just woke up", "I just had a meal", "I should not have eaten XX", "I just had a bowel movement", "I'm going home now", etc. Alternatively, determination may be made based on items acquired by a sensor.

Next, monitor constipation risk and polyplast risk (S7). If you are going to have a colonoscopy, take a laxative and cleanse your bowel before undergoing the colonoscopy. For subjects with constipation symptoms, the usual amount of laxative may not be sufficient for intestinal cleansing or may require a long time for intestinal cleansing. needs good advice. Therefore, in this step, the constipation/polyprisk determination unit 14 determines whether the subject is at risk of constipation based on the subject's profile determined in step S3 and the subject's lifestyle habits determined in step S5. Determine if you have This determination may be made by providing an inference engine in which an inference model is set in the constipation/polyprisk determination unit 14 in the service server 10 . The inference model used in this case will be described later with reference to FIG. In addition, the determination may be made logically using information acquired in profile determination or lifestyle determination (see S3 and S5), without being limited to inference. This determination will be described later with reference to FIGS. 11 to 12D.

Also, in step S7, the risk of lesions such as polyps is monitored. A lesion such as a polyp may be found during an endoscopy, and a treatment to remove the lesion such as the polyp may be performed. In this case, the treatment may take a long time, and the time planned by the subject may be exceeded. Therefore, it is desirable to improve lifestyle habits so that the risk of lesions such as polyps does not occur, and lesions may disappear by improving lifestyle habits. Therefore, in step S7, the control unit 21 determines whether the subject has polyplast risk based on the subject's profile determined in step S3, the subject's lifestyle habits determined in step S5, and the like. determine whether This determination may be made by providing an inference engine in which an inference model is set in the constipation/polyprisk determination unit 14 in the service server 10 . The inference model used in this case will be described later with reference to FIG. In addition, the determination may be made logically using information acquired in profile determination or lifestyle determination (see S3 and S5), without being limited to inference. This determination will be described later with reference to FIGS. 13 and 14. FIG.

Next, it is determined whether or not it is a specific timing (S9). For example, the schedule management unit 13 (or the control unit 11) determines the timing based on the profile determination result of the user of the user terminal 20, the lifestyle habit determination result, and the like. This timing may be every day, or may be the timing of a physical examination (for example, once a year). Alternatively, the timing may be the timing at which the user is recommended to undergo an endoscopy or the like based on the past medical examination history or the like. When the endoscopy examination timing comes, the schedule management unit 13 causes the UI unit 25 to display information recommending the user to undergo the endoscopy. In addition, when the user has made an appointment at a medical facility or the like and the time is approaching, a message to that effect may be displayed. If the result of determination in step S9 is that it is not the specific timing, the process returns to step S1. Returning to step S1, the aforementioned profile determination and lifestyle habit determination are performed, and thereafter, the constipation risk and polyprick risk are monitored. Therefore, every time steps S1 to S9 are executed, the above risks are monitored.

On the other hand, if the result of determination in step S9 is the specific timing, the constipation risk and polyplast risk are determined (S11). As described in step S7, if the subject tends to be constipated, it takes time to clean the intestine. Since the condition of constipation may be improved by improving lifestyle habits, etc., in this step, the constipation/polyply risk determination unit 14 determines the most recent constipation risk. In addition, if the subject has polyps in the intestine, the examination time may exceed the subject's expectations due to the time it takes to treat the polyps. is also determined. These determinations are made based on the monitoring results of constipation risk and polyprick risk in step S7.

Next, display improvement advice (S13). In step S9, since the constipation risk and polyprick risk are determined at a specific timing (see S11), in step S13, the risk reduction proposal unit 15 creates improvement advice based on the constipation/polyprisk determination. and displayed on the UI unit 25 of the user terminal 20 through the communication unit 12 . If the risk of constipation or polyps is high, advice may be given to reduce these risks. In addition, when undergoing an endoscopy, improvement advice for shortening the examination time is displayed. For example, in the service server 10 or the like, the cloud doctor may display advice to the subject, such as "In your case, if you do it here, it will be over in no time."

Further, although the specific timing will be described later, it may be once or several times a day. At this timing, based on the items determined in steps S3 and S5, it is possible to present improvement advice to the user. good. For example, as a result of determining lifestyle habits, if exercise is insufficient, if sleep time is short, if specific nutrients are low, or the like, advice that can improve the health condition may be given. Further, the improvement advice may change over time from when the subject starts the improvement activity until the actual examination date. In other words, at the start of improvement and immediately before taking an examination, the advice should be suitable for that period. In addition, even if there is no constipation/polyprick risk, it is possible to provide advice such as knowledge that should be known before taking the test.

Next, an inspection time guide is displayed (S15). In this case, the control unit 11 cooperates with the schedule management unit 13, the constipation/polyprisk determination unit 14, and the time prediction unit 17 to display the time when the test can be taken in consideration of the request of the subject. . When the risk of constipation or polyposis is low, this examination timing is determined based on the results of searching for availability of medical facilities where examination is possible. On the other hand, when the risk of constipation or polyposis is high, the timing when these risks can be reduced is predicted, and based on the prediction results, a guidance display for examination timing is displayed. For example, even in the case of a subject with a risk of constipation, if the risk of constipation is reduced by improving their eating habits, a message such as "It has been improved, why don't you make an appointment now?" You may go to the UI section 25 . Also, if the examinee is likely to have polyps, it is possible to display a message such as "I think there may be polyps, but this hospital will treat them without hospitalization, so how about this time of year?" good. The detailed operation of the examination time guide display in step S15 will be described later with reference to FIG.

In addition, the time required for the examination varies depending on the method and congestion of the hospital where the examination is performed. In this step, the control unit 11 displays the examination time in consideration of the acquired hospital congestion status, treatment time, treatment policy, etc. through the communication unit 12 . For example, if you want the treatment to be completed in a short time, if you want the examination start date to be close, or if you want a hospital that has a high reputation among users, choose a hospital that meets the needs of the subject. The inspection time is displayed while taking into consideration. It is preferable to display the guide display of the examination time on the UI unit 25 of the user terminal 20 .

Next, it is determined whether or not to make a reservation (S17). When the subject looks at the guide display of the examination time and makes a reservation, he or she indicates the intention of making the reservation through the UI unit 25 of the user terminal 20 . In this step, the control unit 11 determines whether or not the subject has instructed an appointment. If there is no declaration of intention to make a reservation, the process returns to step S1.

On the other hand, if there is an intention to make a reservation in step S17, candidate institutions are displayed and reservation processing is executed (S19). Here, candidate institutions (medical institutions, etc.) that match the inspection time displayed in step S15 are displayed. That is, candidate institutions that are available for inspection near the inspection time displayed in step S15 are displayed. An examination such as an endoscopy is reserved for a medical facility selected by the subject from among these candidate institutions. When the controller 11 in the service server 10 receives the subject's intention to make a reservation, it notifies the schedule management units 32 and 37 of the hospital systems 30 and 35 of the reservation through the communication unit 12 . If the reservation is made, it is displayed on the UI section 25 of the user terminal 20 . When the reservation process is completed, the process returns to step S1.

In this way, in the flow of the examination assistance application, examination risks such as constipation risk and polyprick risk are constantly monitored based on the subject's profile and lifestyle (see S1 to S7). If there is constipation, the inside of the intestine is not easily cleaned, which is an unfavorable situation for endoscopic examination, and it is difficult to enter the examination. In addition, the presence of polyps affects treatment during endoscopic examination, and the presence of polyps requires time and effort such as excision and hemostasis, which affects examination time. In other words, if there are these risks, the time to be restrained for the examination will be longer, and if treatment such as polyp removal and hemostasis is performed, there will be dietary restrictions after the examination, which will put stress on the examinee. . Of course, the same is true for the medical staff performing the examination. Therefore, if it is not chronic, it can be said that it is preferable for both the subject and the medical staff to perform the examination after the risk is eliminated.

Therefore, in this embodiment, at a specific timing such as an annual health checkup, the physical condition of the subject is adjusted to a state in which examination stress is low. By adjusting the schedule on the hospital side, it is possible to perform examinations in favorable conditions for both the subject and the medical staff. Note that the specific timing in step S9 of FIG. 3 may be changed according to the situation. For example, when a regular health checkup is performed in May, the specific timing is often reserved around April of the previous month, so April is the specific timing. After that, when the date and time of the health checkup is approaching, the specific timing becomes timing such as every week or every day in order to confirm daily changes in the risk of constipation or the like. At this specific timing, risk is determined and improvement advice is provided.

In the flow of the test assistance app, at a specific timing based on regular health checkups, etc., test risks such as constipation risk and polyprick risk are determined, and based on the results of this determination, measures are taken to reduce test risks. Improvement advice is provided to the subject (see S9 to S13). Considering the risk of constipation and the risk of polyps, a guide display of when to undergo an endoscopy is performed (see S15). Even if there is an inspection risk at present, by executing the improvement advice, it is possible to receive the inspection at a time when the inspection risk is reduced. When this examination risk is reduced, medical facilities where examination is possible are searched and displayed (see S17 and S19). Therefore, the subject can be tested when the risk of testing is low.

In this way, at the specific timing in step S9, advice is frequently provided so that the subject is in the best possible state during the examination (target schedule) (see S13). However, if the subject's condition does not improve at all, in "Constipation/polyprisk determination" in step S11, while observing the progress of improvement, advice is given each time a meal is taken or when water should be supplied. may be provided. If there is no improvement by modifying such a moderate diet, it is determined by the direction and degree of change in the results of risk determination evaluated by the numerical values described later. For example, if there is no improvement at all and the rate of deterioration is rather fast, you can immediately consult a doctor at a convenient time based on the hospital's schedule information. good. In other words, chronological advice uses judgments such as the direction, speed, and degree of change in risk over time, and makes judgments based on the difference between the previous risk value (recorded) and the current risk value. .

For example, if the advice to increase fluid intake does not produce positive results, the following advice may be used to increase fluid intake, but the amount of exercise and a regular lifestyle are not recommended for other people of similar age and gender. By also making a judgment as to how it compares with , if you lack exercise, you may be encouraged to exercise, or you may be encouraged to sleep regularly. In addition, the same advice to increase water intake may be given, or advice to drink water as soon as the subject wakes up in the morning may be given. The timing at which such advice should be given is also the specific timing described above. If the deadline is approaching or if improvement is not expected, a mild magnesium-based drug may be recommended. good too. It prioritizes a natural diet and exercise without relying on drugs.

In this way, advice is given while confirming the improvement of the situation over time, so this is called advice over time. That is, the chronological advice consists of a target schedule (a schedule is a specific schedule or plan made in advance, or a table describing it, a schedule, or a schedule, but in this case, the former), and an inspection risk. Switch between multiple advices depending on the situation. The stress given to the subject differs depending on whether the subject is quickly given a laxative or slowly instructed to eat. Also, the chronological advice determines the effect of the advice according to the improvement of the test risk, and switches between the plural advices. Whether or not the advice is effective may be determined by answering a questionnaire, or by analyzing information from a pedometer or heart rate monitor using a wearable sensor or the like and making a decision by action determination.

If the subject behaves as advised but does not improve, different advice may be provided according to pre-programmed improvement measures based on specific rules. Alternatively, it may be possible to determine what kind of advice was most effective from changes in the risk data of the examinee or a person who has a profile similar to that of the examinee, and reflect it in the advice. As will be described later, risk is affected by gender, age, genetics, etc. Since these factors are difficult to improve, other risk factors are reduced. Since these risks are quantified in FIGS. 12A to 12E, for example, risk can be reduced by referring to them.

In this way, the above-mentioned advice is given to the mobile terminal of the user. Focusing attention, this embodiment includes the following inventions. In other words, the present embodiment includes a user information acquisition unit that acquires profile information and lifestyle information of a mobile terminal user (for example, lifestyle acquisition unit 24 in FIG. 1, see S1 to S5 in FIG. 2), There is a correction determination unit that determines a correction point for reducing the difference in lifestyle habits information corresponding to the constraint that occurs when undergoing a clinical examination, albeit in cooperation with an external device. (See, for example, the UI unit 25 in FIG. 1 and S11 and S13 in FIG. 2). When a subject undergoes a clinical examination, if there is a risk of constipation, polypricks, or the like, the examination will be time-consuming. Therefore, in the present embodiment, correction points/advice for correcting/improving lifestyle habits that have caused restrictions are displayed.

In another expression, the lifestyle information acquired at that time and the better lifestyle information (this is Information on an ideal life, an average life, and a life with good test results are recorded and can be compared), and a correction determination unit that determines correction points to reduce the difference. It includes the invention of a terminal. Since the display unit may transmit by voice, it may be called a transmission unit. The correction determination unit can also be called an advice unit. An application or the like may be built in the mobile terminal, and the application or the like may output advice. A cloud service may have this function.

Here, we explained from the perspective of a mobile terminal, but it goes without saying that the above technical features are also present in the linked server. This embodiment includes a user information acquisition unit that acquires the mobile terminal user's profile information and lifestyle information from the mobile terminal, and the lifestyle information that corresponds to the restrictions that will occur when undergoing a specific clinical examination in the future. and a transmission unit for transmitting advice information so that the mobile terminal can display or notify the correction points. I'm in.

Next, using the flowchart shown in FIG. 3, the detailed operation of displaying the examination time guide in step S15 (see FIG. 2) will be described. When the examination time guide display flow starts, first, the constipation risk and defecation tendency are determined (S21). Here, the constipation/polyprick risk determination unit 14 determines the constipation risk and defecation tendency based on the constipation risk determination results in steps S7 and S13 and the lifestyle habit determination result in step S5. The determination of constipation squirrel may be performed logically, but since there are various factors, AI (Artificial Intelligence) may be used to make inferences. Generation of an inference model used when AI is used will be described later with reference to FIG. A method for logically determining the risk of constipation will be described later with reference to FIGS. 11 and 12A to 12E.

Next, it is determined whether or not there is room for improving constipation (S23). Here, the constipation/polyprisk determination unit 14 (or the control unit 11 may be used) determines whether or not constipation can be improved based on the determination result in step S21. For example, if the intake of dietary fiber is predicted based on the content of the meal, and constipation tends to occur due to a small amount of dietary fiber, constipation may be alleviated by increasing the intake of dietary fiber. Similarly, when the amount of water intake is low, constipation may be improved by increasing the amount of water intake. Furthermore, even if the amount of exercise is low, increasing the amount of exercise may improve constipation. In addition, when a state of high stress (high blood pressure, rapid pulse, etc.) continues, there is a possibility that constipation can be improved by maintaining a state of relaxation and low stress.

As a result of the determination in step S23, if there is no room for improvement of constipation, the possibility of polyps is inferred based on the profile and lifestyle (S25). Here, using the subject's profile determined in step S3 and the lifestyle information determined in step S5, the constipation/polyp risk determination unit 14 infers whether or not the subject has polyps. . As described above, if the subject has polyps, it takes time to treat the polyps, which lengthens the examination time as a whole. Therefore, in this step, it is inferred whether or not there is a polyp. Generation of the inference model for this inference will be described later with reference to FIG. Determination of polyprisk is not limited to inference, and may be determined logically. The logical determination will be described later with reference to FIGS. 13 and 14. FIG.

Next, it is determined whether there is a possibility of improvement of polyps, etc. (S27). Here, the constipation/polyp risk determination unit 14 (or the control unit 11 may be used) determines whether or not there is a possibility of improving polyps or the like based on the inference result in step S25. For example, when a diet containing a lot of animal protein and fat is continued, the risk of developing lesions such as polyps is high. The same is true when the amount of exercise is small. Therefore, depending on the characteristics of lifestyle habits, it may be improved by reducing animal protein and fat intake, consuming more vegetables, and increasing the amount of exercise.

If the result of the determination in step S23 is that there is room for improvement in constipation, or if the result of the determination in step S27 is that there is a possibility of improving polyps or the like, the possibility of improvement is displayed and an instruction for improvement is given ( S29). Here, the risk reduction proposal unit 15 gives advice for improving constipation to the subject through the user terminal 20 . For example, it advises on the content of meals such as foodstuffs, rehydration, and medication as necessary. If a hospital appointment is made in step S17 (see FIG. 2), the advice frequency and advice content may be changed in accordance with the date and time of the appointment.

In step S29, if an instruction for improvement is issued, or if the result of determination in step S27 is that there is no possibility of improvement of polyps, etc., the possibility of improvement prediction is determined (S31). Here, the control unit 21 makes a determination based on whether improvement is predicted as a result of the determinations in steps S23 and S27 (S31). In step S31, if the risk of constipation or polyploidy is already sufficiently low, it is difficult to reduce the risk any further, so a negative (NO) determination is made.

As a result of the determination in step S31, if it is determined that there is a possibility that improvement can be predicted, a nearby medical facility that has an examination vacancy after the predicted date and time and at a timing close to the timing of the regular examination is searched ( S33). Here, the schedule management unit 13 in the service server 10 cooperates with the in- hospital systems 30 and 35, close to the date of the regular examination, after the date when constipation is expected to be improved, and moreover, the subject's Find medical facilities near you that have openings for testing. When the search is successful, the control unit 11 causes the UI unit 25 to display the search results.

On the other hand, if the result of determination in step S31 is that it is not possible to predict improvement, a nearby medical facility with vacancies for examinations is searched for at a timing close to the time of regular examinations (S33). Here, the schedule management unit 13 in the service server 10 cooperates with the in- hospital systems 30 and 35 to provide medical services that are close to the time of regular examinations, are near the subject, and have available examinations. Search for facilities. When the search is successful, the control unit 11 causes the UI unit 25 to display the search results.

In steps S33 and S35, when the medical facility is searched and the search results are displayed, the flow for displaying the examination time guide is terminated and the original flow is returned to.

In this way, in the flow of examination time guide display, consideration is given to room for improvement of constipation (see S23) and room for improvement of polyps and the like (see S27), and if there is room for improvement, advice for improvement is given. (see S29). Therefore, it is possible to appropriately prepare for an examination such as an endoscopic examination, and the subject can receive a medical examination without worry. In particular, if there is a risk of constipation or polyps, it is possible to undergo the examination after reducing these risks.

In addition, in the flow shown in Fig. 3, if there is room for improving constipation, the possibility of improving polyps, etc. is not determined. However, even if there is room for improvement in constipation, it may be determined whether or not there is room for improvement in polyps, etc., and if there is room for improvement as a result of the determination, advice for improvement may be proposed for polyps as well.

As described above, in the first embodiment of the present invention, the service server 10 that provides examination support cooperates with the user terminal 20 possessed by the subject to reduce the constipation risk of the subject. The cleaning risk and polyprick risk are determined (see, for example, S7 and S11 in FIG. 2), and if these risks exist, advice for improvement is given (see, for example, S11). In this way, it is possible to receive advice on taking therapeutic drugs (for example, laxatives, etc.) prior to the examination and on physical condition management before coming to the hospital, so that the patient can undergo an appropriate examination. Furthermore, when these risks are reduced or when these risks are known, examinations such as endoscopy can be performed.

It should be noted that the flowcharts shown in FIGS. 2 and 3 have been described as being executed mainly by the control unit 11 in the service server 10 in cooperation with the user terminal 20 and the hospital systems 30 and 35 . However, without being limited to the service server 10 , the user terminal 20 may be the main body and may be executed in cooperation with the service server 10 and the hospital systems 30 and 35 . In this case, all or part of the functions of the schedule management unit 13, the constipation/polyprisk determination unit 14, the risk reduction proposal unit 15, the hospital policy confirmation unit 16, the time prediction unit 17, etc. in the service server 10 can be used by the user. It should be held in the terminal 20 . In other words, the user terminal 20 proactively performs profile determination, lifestyle determination, constipation/polyprisk determination, determination of specific timing, generation of improvement advice, prediction of examination timing, reservation processing of an examination institution, etc. (see FIG. 2). processing, and the service server 10 may simply assist the user terminal 20 . Of course, the processing contents may be distributed so that only a part of the processing in FIGS.

In addition, in the present embodiment, the case where the subject is constipated has been mainly described as the cleaning risk. However, cleaning risk is the risk of cleaning the intestinal tract before undergoing an endoscopy. If there is a possibility of occurrence, it may be dealt with in advance. Regarding the cleaning risk, the same applies to the second embodiment described later.

Next, an endoscopy support system according to a second embodiment of the present invention will be described using FIGS. 4 to 6. FIG.

FIG. 4 is a block diagram showing the overall configuration of the endoscopy support system according to the second embodiment. This endoscopy support system has a service server 10, a user terminal 20, and in- hospital systems 30 and 35, as in the first embodiment. have

That is, the service server 40 is a server for providing general health services to the user terminal 20. In the present embodiment, the service server 10 provides support for endoscopic examination through application software used by the user for providing health services. The service server 40 constantly acquires vital information such as body temperature, pulse, and blood pressure from the user's wearable terminal, and gives health advice to the user based on this information. As health advice, a database (DB) recording prescriptions corresponding to vital data may be provided, and advice may be provided to the user by searching this DB.

The endoscopy support system according to the second embodiment differs from the first embodiment in that only the service server 40 is added, so the service server 40 will be mainly described. The service server 40 has a control section 41 , a communication section 43 , a profile management section 43 , a situation confirmation section 44 , a health advice section 45 and a service cooperation section 45 . Note that the profile management unit 43, the status confirmation unit 44, the health advice unit 45, and the service cooperation unit 46 may be realized by hardware circuits or the like, and the control unit 41 may execute a program stored in the memory. , can be realized.

The control unit 41 controls the service server 40 as a whole. The control unit 41 has a processing device such as a CPU, a memory storing a program, and the like, and can execute the program and control each unit in the service server 40 .

The communication unit 42 has a communication circuit provided within the peripheral circuit, and can communicate with each communication unit within the user terminal 20 and the service server 10 . Communication is also possible with the communication units in the hospital systems 30 and 35 through the communication unit 12 in the service server 10 .

The profile management unit 43 manages profiles of users who use health assistance applications provided by the service server 40. The user's profile includes the user's name, age, sex, address, email address, past medical history, past vital data, smoking tendency, drinking tendency, food preferences, and the like. The profile management section 43 records these information and updates the information.

The situation confirmation unit 44 collects information about the situation of the user using the user terminal 20. As for the user's situation, for example, using a positioning system such as GPS (Global Positioning System), it is possible to grasp the user's behavior based on the user's position and its change over time. In addition, the user's condition includes vital information such as blood pressure, pulse, and body temperature measured by a wearable terminal or the like. In addition, the user's health condition can also be grasped from an image captured by the imaging unit of the user terminal 20, for example, the state of defecation. Furthermore, information posted by the user to SNS or the like can also be used when judging the user's situation. In this way, the situation confirmation unit 44 can confirm the user's situation by various means. By analyzing the above data, situations such as before going to bed, after waking up, eating, drinking water, defecating, and exercising can also be determined. If meal-specific situations occur regularly, advice can be provided at pre-meal timing, such as what to eat more or to eat slowly. If we know the wake-up situation, we can advise you to drink a glass of water when you wake up.

The health advice unit 45 uses the information acquired by the profile management unit 43 and the situation confirmation unit 45 to output general health advice to the user. This health advice may be presented according to the user's situation, etc., by creating a database in advance, searching this database, and presenting health advice that matches the situation, etc. For example, if you have recently gained weight, you may be advised to lose weight for health reasons. Also, if sleep time is not enough, advice to recommend taking sleep may be given. In addition, if the temperature is above normal, it may be recommended to see a doctor. In addition, health advice is not limited to a database, and an inference model may be used to obtain an inference result, and based on this inference result.

The service cooperation unit 46 allows the service server 40 to cooperate with the user terminal 20, the service server 10, the hospital systems 30 and 35, and the like. For example, various information is acquired from the user terminal 20, and based on this information, the health advice section 45 cooperates so that health advice can be output to the user terminal 20. FIG. Furthermore, based on the information from the user terminal 20 , the service server 10 may be requested to determine the risk of constipation or polyprickly risk, and the result thereof may be output to the user terminal 20 . Similarly, a proposal (advice) from the risk reduction proposal unit 15 of the service server 10 may be output to the user terminal 20 . Furthermore, the service cooperation unit 46 includes the user terminal 20, the service server 40, the service server 10, The hospital systems 30 and 35 may be communicated with each other.

Next, the operation of the health assistance application will be described using the flowchart shown in FIG. 5(a). In this health assistance application, the service server 40 cooperates with the user terminal 20 to give general health assistance advice to the user. Similar to the flow of FIG. 2, the flow of the examination assistance application shown in FIG. 6 provides advice when undergoing an endoscopy, while the flow shown in FIG. Provide advice to users. The health assistance application is executed by the control unit 41 of the service server 40 according to a program stored in the service server 40 and causes the user terminal 20 to display general health advice.

When the operation of the flow shown in FIG. 5(a) starts, first, a questionnaire is displayed and the input made by the user is determined (S41). Here, as in step S1, the control unit 41 of the service server 40 causes the UI unit 25 to display information about the subject and a screen for inputting preferences and tastes of the subject that are necessary for examination. display. When the subject inputs questionnaire items on this screen, the items are transmitted to the service server 40 through the communication unit 22, the control unit 41 determines the input items, and records the determination items in the recording unit. The questionnaire may include the subject's name, sex, age, medical history, past examination history, and the like. Also, when performing an endoscopy, in step S41, similarly to step S1, information to be used when performing an endoscopy may be input.

Next, profile determination is performed (S43). Here, as in step S3, the profile management unit 43 (or the control unit 41) stores the results of the questionnaire in step S41, the user profile information recorded in the recording unit in the user terminal 20, and the A subject's profile is determined based on the user's health information recorded in a server or the like. The profile includes basic information such as the subject's name, sex, age, etc., and medical-related information such as past diseases may also be determined. In addition, if a second opinion on the user is recorded on a cloud server or the like, it may be used.

Next, determine your lifestyle habits (S45). Here, the situation determination unit 44 (or the control unit 41) determines the lifestyle habits of the user using the user terminal 20, as in step S5. This determination is made based on the user's lifestyle information collected by the lifestyle acquisition unit 24 in the user terminal 20 .

Next, share related information (S47). Here, related information is shared with the inspection assistance application shown in FIG. That is, among the information determined in steps S41, S43, and S45, information related to examinations such as endoscopy is shared with the service server 10. FIG. In step S61 (see FIG. 6), which will be described later, the control unit 41 allows the health assistance application and the examination assistance application to share information held by each application in relation to each other.

Next, it is determined whether it is a specific timing or a specific situation (S49). Here, the control unit 21 determines whether it is a specific timing or a specific situation. Since this health assistance application provides general health advice to the user, the predetermined timing is the specific timing. For example, it may be once a day at a specific time, or once a week or a month. Further, the timing is not limited to once, and may be multiple timings such as twice a day. Furthermore, the specific timing is not limited to the time, but may be the specific timing when a specific item is determined in input determination, profile determination, or lifestyle habit determination. For example, it may be the timing at which health advice is required, such as when the user determines that exercise is insufficient or that sleep is insufficient based on any of the determinations.

Furthermore, in step S49, it may be determined that it is the specific timing when the situation is such that an examination such as an endoscopy is to be performed. Similar to step S9 described above (see FIG. 2), it may be determined that the time is the specific timing based on the time of diagnosis, the history of past medical examinations, and the like. As a result of this determination, if it is not the specific timing or the specific situation, the process returns to step S41. After returning to step S41, the aforementioned profile determination and lifestyle determination are repeatedly performed.

If the result of determination in step S49 is a specific timing or a specific situation, then related information is collected (S51). Here, in step S47 (see step S61 (FIG. 7)), health-related information is collected in addition to the shared related information.

Next, provide improvement advice, etc. (S53). Here, general advice is given based on the health-related information collected in step S51. Also, if the user is constipated based on their profile and lifestyle habits, advice for relieving constipation is provided. That is, if the information collected in steps S41 to S47 indicates that the user is constipated, advice for constipation is displayed on the UI section 25 of the user terminal 20, as shown in FIG. 5(b). In this example, the advice "Let's eat a lot of vegetables" is given as a dietary content to relieve constipation.

Also, in step S53, if the time for the user's physical examination is approaching, advice may be given to encourage the user to get well and undergo an endoscopy, as shown in FIG. 5(c). Further, even if advice to improve physical condition is suddenly given, if there is no space in the examination schedule of the hospital, unreasonable adjustment will be forced unnecessarily. Therefore, the method of giving advice may be adjusted depending on whether the examination schedule is checked and whether there is a vacancy two weeks ahead or a month later. In this case, there may be several candidates, and if the user touches "start guidance", it may be possible to select from among a plurality of options when giving advice when performing an endoscopy. good. In this case, in cooperation with the examination assistance application shown in FIG. That is, the improvement advice given in this step is also shared with the inspection assistance application (see S65 in FIG. 6). The schedule proposal unit may propose a plurality of candidates for the period when the examination risk is reduced according to the situation of the examination facility. In addition, further recommendations may be made from a plurality of candidates according to the subject's condition. After providing the improvement advice, the process returns to step S41.

In this way, the health assistance application shown in FIG. 5 normally determines the user's profile and lifestyle habits (see S41-S45), and provides general health advice based on this information (S51). Then, when the user undergoes an endoscopic examination or when the user is constipated, various advices are provided to the user in cooperation with the examination assistance application shown in FIG. The user can receive advice from the examination assistance application described in the first embodiment while using a normal health assistance application. That is, similar services can be received without starting two applications.

Next, the operation of the inspection assistance application will be described using the flowchart shown in FIG. This flow is a flow for giving advice and support so that the subject can easily undergo the examination when performing an examination such as an endoscopy. This examination assistance application is executed by the control unit 11 in the service server 10 according to a program stored in the service server 10, and operates in cooperation with the user terminal 20 through the service cooperation unit 46 of the service server 40. .

When the operation of the flow shown in FIG. 6 starts, first, related information is shared (S61). Here, the health-related information collected by the health assistance application shown in FIG. 5 is acquired, and the information collected by the health assistance application is provided to the health assistance application (see S47 in FIG. 5). Also, health-related information may be collected not only from the user terminal 20 but also from the service server 40, the in- hospital servers 30 and 35, and the like.

Next, the constipation risk and polyprick risk are determined (S63). Here, similarly to steps S7 and S11 (see FIG. 2), the constipation/polyprick risk determination unit 14 determines constipation risk and polyprisk risk based on the related information shared in step S61.

Next, the improvement advice information is shared (S65). Here, the improvement advice (see S53 in FIG. 5) provided to the user by the health assistance application is shared. This is because if there is advice on the user's lack of exercise, lack of sleep, obesity, etc., it may be useful for advice when taking an examination.

Next, the inspection guide information is shared (S67). Here, the improvement advice provided to the user by the examination assistance application is also shared with the health assistance application. For example, the health assistance application is provided with advice to be provided when undergoing an examination such as an endoscopy. With this advice, the health assistance application can provide the user with advice on the premise of undergoing an examination such as an endoscopy. Also, as test information, other servers may have test results such as blood tests, and such information may also be shared.

Next, it is determined whether or not it is a reservation (S69). Here, similarly to step S17 in FIG. 2, it is determined whether or not it is time for the user to undergo an examination such as an endoscopy. The information collected by the health assistance application is also shared with the examination assistance application (S47, S51 in FIG. 5, and S61 in FIG. 6). Based on this information and the information collected by the examination assistance application, it is determined in step S69 whether or not it is time for examination. Note that this appointment is not limited to a new appointment, and whether or not it is time for a reexamination may also be determined. If the result of determination in step S69 is that it is not the reservation timing or the like, the process returns to step S61.

If the result of determination in step S61 is a reservation, candidate institutions are displayed and reservation processing is performed (S71). Here, similarly to S19 in FIG. 2, candidate institutions (medical facilities, etc.) that match the inspection time determined in step 69 (S49 in FIG. 5) are displayed. That is, candidate institutions that are available for inspection near the inspection time are displayed. An examination such as an endoscopy is reserved for a medical facility selected by the subject from among these candidate institutions. This reservation is transmitted to the schedule management units 32 and 37 of the hospital systems 30 and 35 through the service servers 40 and 10, respectively. If the reservation is made, it is displayed on the UI section 25 of the user terminal 20 through the service servers 10 and 40 . When the reservation process is completed, the process returns to step S1.

In this way, the health assistance application and the examination assistance application according to the second embodiment cooperate with each other and contribute to the health promotion of the user. That is, the health assistance application is in charge of general health advice and the like, and the inspection assistance application is in charge of examinations such as endoscopy.

Next, using the flow shown in Fig. 7, generation of an inference model for constipation prediction will be explained. This inference model may be used when determining the risk of constipation in step S7 of FIG. 2 and step S63 of FIG. There is a method for logically determining the constipation risk without using an inference model, but it may also be determined by an inference engine that sets an inference model. For this purpose, for example, a neural network for generating an inference model may be provided in the service server 10, and the constipation/polyprisk determination unit 14 may generate an inference model by deep learning. Also, the inference model generated by the flow of FIG. 7 is set in the inference engine to determine constipation risk. An inference engine may be provided in the user terminal 20 and inference may be made there. Here, the flow of the constipation prediction AI shown in FIG. 7 will be described as being generated by a neural network provided within the constipation/polyprisk determination unit 14 within the service server 10 . Of course, the inference model may be generated in, for example, the control unit 11 in the service server 10 or a server other than the service server 10 .

When the constipation prediction AI flow shown in FIG. 7 starts, first, the profile, lifestyle habits, and eating habits data are obtained through questionnaires, etc. (S81). Here, the constipation/polyprisk determination unit 14 in the service server 10 acquires user profiles, lifestyle habits, and eating habit data from a large number of user terminals 20 and the like through questionnaires and the like. As described above, the user terminal 20 performs questionnaire input, profile determination, and lifestyle habit determination (see S1 to S5 in FIG. 2). good too. Also, information posted on SNS or the like on the Internet that includes information about constipation may be collected.

Next, a survey is conducted on whether or not the subject is constipated, and the results are annotated to the data acquired in step S81 to generate teacher data (S83). Here, the constipation/polyprisk determination unit 14 requests the user terminal 20 to conduct a questionnaire about whether or not the user is likely to be constipated. For example, when the questionnaire is displayed in S1 of FIG. 2, S41 of FIG. 5, etc., the constipation/polyprisk determination unit 14 requests the user terminal 20 to display a question as to whether or not the subject is likely to be constipated.

In step S83, when the result of the questionnaire about whether or not the subject is constipated is acquired, the data obtained in step S81 is annotated with the result of the questionnaire regarding whether or not the subject is likely to be constipated to create training data. For example, data such as meal content, age, sex, exercise status, etc. are annotated with information as to whether or not the subject is likely to be constipated.

Next, deep learning is performed (S87). Here, the constipation/polyprick risk determination unit 14 inputs training data to the neural network and determines weighting of the middle layers of the neural network so as to obtain a result of whether or not the subject is likely to be constipated. Deep learning is performed using a large amount of teacher data. In FIG. 7, it is described that learning is performed each time teacher data is created. In addition, learning may be performed.

After learning is performed in step S87, it is next determined whether or not the reliability is OK (S87). Here, the constipation/polyprick risk determination unit 14 determines whether or not the output when image data for reliability confirmation whose answer is known in advance is input to the generated inference model is the same as the answer. to determine reliability. If the confidence of the inference model created is low, the proportion of matching answers is low. If the reliability value is higher than a predetermined value, the reliability is determined to be OK.

If the result of determination in step S89 is that the reliability is not OK, the teacher data is sorted out (S91). If the reliability is low, the reliability may be improved by selecting the teacher data. Therefore, in this step, the constipation/polyprisk determination unit 14 selects additional information. Information (teaching data) is added in order to improve reliability. At this time, the control unit 1 selects information that is likely to have a causal relationship with constipation. In addition, the constipation/polyprick risk determination unit 14 may exclude data that have no causal relationship. In this process, an inference model for inferring the causal relationship is prepared, and supervised data with a high causal relationship is automatically added, and supervised data with a low causal relationship is automatically excluded. . Also, the condition of the population of training data may be changed. After selecting the teacher data, the process returns to step S87 to create an inference model again.

On the other hand, if the reliability is OK as a result of the determination in step S89, an inference model is created (S93). Here, since the reliability of the constipation prediction inference model generated in step S87 is high, it is determined as the inference model. In addition, the specification information is attached to this inference model. The specification information includes specifications such as the number of intermediate layers in the neural network, the mother set of training data used to generate the inference model, and information on evaluation data used to evaluate reliability. . The inference model generated here is set in the inference engine of the constipation/polyprisk determination unit 14 . In addition, if the user terminal 20 has an inference engine, it may be transmitted to the user terminal 20 . The user terminal 20 may set the received inference model in the inference engine and predict the constipation risk using the constipation prediction AI when determining the constipation risk. When the inference model is completed, the constipation prediction AI flow ends.

Next, generation of an inference model for polyp prediction will be described using the flow shown in FIG. This inference model may be used when determining polyprisk in step S7 of FIG. 2 and step S63 of FIG. As with the risk of constipation, polyprisk can be determined logically without using an inference model, but may be determined by an inference engine with an inference model set. For this purpose, for example, a neural network for generating an inference model may be provided in the service server 10, and the constipation/polyprisk determination unit 14 may generate an inference model by deep learning. Note that an inference engine may be arranged in the user terminal 20, an inference model generated by the flow of FIG. 8 may be set, and the polyprisk may be determined. Of course, the inference model may be generated in a server or the like other than the service server 10 .

When the constipation prediction AI flow shown in FIG. 8 starts, first, when a polyp is discovered, a doctor, medical worker, or endoscope transmits polyp information and a patient ID (S82). A polyp is generally discovered by a doctor or the like during an endoscopy. Therefore, when a doctor or the like discovers a polyp during an endoscopy, information is transmitted to the service server 10 through the hospital servers 30, 35, and the like. If the information cannot be transmitted to the service server 10 in real time, it may be transmitted by batch processing or the like. Also, the service server 10 may collect information about the polyp of the patient ID uploaded to a server on the Internet.

Next, the profile, lifestyle habits, and eating habits data of the patient with the corresponding ID are obtained through questionnaires, etc., annotated on this data, and teacher data is created (S84). Here, the constipation/polyply risk determination unit 14 collects profile, lifestyle, and eating habit data related to the patient ID in which the polyp was discovered. In step S81 described above, if data and the like are acquired for the patient ID, the data may be used. If the data has not been acquired, the constipation/polyprisk determination unit 14 requests the user terminal 20 having the patient ID to send the profile information, and asks the user terminal 20 having the patient ID to send the profile information, as in step S81. Request a survey. For example, the timing of displaying the questionnaire in step S1 of FIG. 2, step S41 of FIG. 5, etc. may be used.

In step S84, when the patient ID profile, lifestyle habits, and eating habits data are acquired, next, the discovery of a polyp is annotated to these data to create teacher data. Also, even if no polyp is found during the endoscopic examination, the subject's profile, lifestyle, and eating habit data are annotated to the effect that no polyp is found, and training data is created.

　In step S84, when the teacher data is created, learning, reliability determination, etc. are performed in step S87 and subsequent steps. Since the operations in steps S87 to S93 are the same as the operations in the corresponding steps in FIG. 7, detailed description thereof will be omitted.

In step S93, when the inference model with specification information is completed, the generated inference model is set in the inference engine within the constipation/polyprick risk determination unit 14. If the user terminal 20 has an inference engine, it may be transmitted to the user terminal 20 and inferred by the user terminal 20 . When the inference model is complete, the polyp prediction AI flow ends.

Next, using the flow shown in Fig. 9, the generation of an inference model for predicting the time to improve constipation will be explained. This inference model may be used when determining whether or not the improvement timing can be predicted in S31 of FIG. In step S49 of FIG. 5(a), it may be determined whether or not the situation is at a specific timing, and may be used in providing improvement advice in step S53. At the time of determining whether or not, the timing for relieving constipation may also be predicted.

As mentioned above, if the subject of the endoscopy is constipated, it may be painful to take a laxative and clean the bowel. In that case, it is desirable to undergo an endoscopy after constipation is improved by improving eating habits and the like. There is a method for logically determining this constipation improvement time prediction without using an inference model (this method will be described later using FIGS. 11 to 12D), but it is determined by an inference engine that sets an inference model. You may For this purpose, for example, a neural network for generating an inference model is provided in the service server 10, and the time prediction unit 17 (or the schedule management unit 13, the constipation/polyprisk determination unit 14) generates an inference model by deep learning. may Moreover, an inference engine is arranged in the time prediction unit 17, an inference model generated by the flow of FIG. 9 is set, and the constipation improvement time is inferred. Of course, the inference model may be generated in, for example, the control unit 11 in the service server 10 or a server other than the service server 10 .

The advantage of using AI when making predictions is that the work of finding effective information as rules from among various information can be entrusted to machines. A method of collecting a large amount of various behaviors represented by the word "lifestyle" in a specific format and turning them into training data can be used. In addition, what you eat is recorded in photographs or the like, and for example, a chronological record of the number of steps taken each day or a chronological change in heart rate is collected for several days, and this collected data is used. You may create training data by This makes it possible to handle exercise patterns, regularity of sleep, eating habits, etc. as data. Also, age, gender, and information about the area in which you live (country, region, living environment, urban or rural, etc.) can be recorded according to a format that determines which data should be written and where. Data conversion is possible. When writing data in a predetermined form or format, it may be possible to automatically use the information of the mobile terminal or wearable device, or use the manually entered information and incorporate it into the format. good too.

When the constipation improvement time prediction AI flow shown in FIG. 9 starts, first, the profile, lifestyle habits, and eating habits data are acquired through questionnaires, etc. (S81). Here, similarly to step S81 in FIG. 7, the time prediction unit 17 (or the schedule management unit 13, or the constipation/polyprisk determination unit 14) in the service server 10 receives user profiles, Data on lifestyle habits and eating habits are acquired through a questionnaire or the like. Since the user terminal 20 performs questionnaire input, profile determination, and lifestyle habit determination (see S1 to S5 in FIG. 2), the time prediction unit 17 may collect these data. Also, information posted on SNS or the like on the Internet that includes information about constipation may be collected.

Next, a survey is conducted to see if constipation is present, and it is determined whether constipation has improved on the same day up to a specific level (from once a week to every day) (S85). Here, it is determined how many days (how many hours) have elapsed since the person (for example, Mr. A) whose profile and the like were acquired in step S81 changed their lifestyle habits, and whether constipation improved. FIG. 10 shows changes in Mr. A's lifestyle (represented by "lifestyle 1" and "lifestyle 2") and her constipation condition (represented by "constipation 1" to "constipation 5"). Mr. A changes from lifestyle 1 to lifestyle 2 at timing T1. The change in lifestyle here refers to the occurrence of differences in water intake, amount of exercise, regular life, and the like. At timing T1, Mr. A's constipation condition was level 5, but by changing his lifestyle, his constipation condition was improved to level 1 at timing T2. It should be noted that the larger the numerical value of the constipation level, the worse the condition. An improvement time Tb until constipation is improved by changing lifestyle habits is determined.

In step S85, if constipation improvement is determined, next, if there is a difference (lifestyle difference) in lifestyle habits and dietary data before and after constipation improvement, improvement time Tb is annotated (S86). Here, the time prediction unit 17 annotates the lifestyle/dietary habit data with the improvement time Tb to create teacher data. Also, even if there is no improvement, an annotation is made to the effect that there was no improvement, and teacher data is created. Since improvement of constipation differs depending on gender, age, etc., in addition to lifestyle habits and eating habits, profile information may be taken into consideration when creating the profile information.

After the teacher data is created in step S86, deep learning is then performed (S87). Here, the time prediction unit 17 inputs teacher data to the neural network and determines the weighting of the middle layer of the neural network so that the constipation improvement time is Tb. Deep learning is performed using a large number of training data. In FIG. 9, it is described that learning is performed each time teacher data is created. Alternatively, you can proceed to the next step. Further, deep learning may be performed for each profile. For example, you may study by dividing into each age group.

When learning is performed in step S85, the processing from step S89 onwards is executed. Since the operations in steps S89 to S93 are the same as the operations in the corresponding steps in FIG. 7, detailed description thereof will be omitted.

In step S93, when the inference model with specification information is completed, the generated inference model is set in the inference engine within the time prediction unit 17. When predicting the improvement time in step S31 of the examination assistance application of FIG. 3, the constipation improvement time prediction AI may be used to predict the constipation improvement time. When the inference model is completed, the flow of constipation improvement time prediction AI ends.

Here, deep learning will be explained. "Deep learning" is a multilayer structure of the process of "machine learning" using neural networks. A typical example is a "forward propagation neural network" that sends information from front to back and makes decisions. The simplest forward propagation neural network consists of an input layer composed of N1 neurons, an intermediate layer composed of N2 neurons given by parameters, and N3 neurons corresponding to the number of classes to be discriminated. It suffices if there are three output layers composed of neurons. The neurons of the input layer and the intermediate layer, and the intermediate layer and the output layer are connected by connection weights, respectively, and the intermediate layer and the output layer are added with bias values, so that logic gates can be easily formed.

The neural network may have three layers for simple discrimination, but by increasing the number of intermediate layers, it is also possible to learn how to combine multiple feature values in the process of machine learning. In recent years, 9 to 152 layers have become practical from the viewpoint of the time required for learning, judgment accuracy, and energy consumption. In addition, a process called "convolution" that compresses the feature amount of an image may be performed, and a "convolution neural network" that operates with minimal processing and is strong in pattern recognition may be used. In addition, a "recurrent neural network" (fully-connected recurrent neural network), which can handle more complicated information and can handle information analysis whose meaning changes depending on the order and order, may be used in which information flows in both directions.

In order to realize these technologies, conventional general-purpose arithmetic processing circuits such as CPUs and FPGAs (Field Programmable Gate Arrays) may be used. However, not only this, but since most neural network processing is matrix multiplication, it is also possible to use processors called GPUs (Graphic Processing Units) and Tensor Processing Units (TPUs) that specialize in matrix calculations. good. In recent years, such artificial intelligence (AI) dedicated hardware "neural network processing unit (NPU)" is designed to be integrated and embedded with other circuits such as CPU, and has become a part of the processing circuit. In some cases.

In addition, there are other methods of machine learning, such as support vector machines and support vector regression. The learning here involves calculation of classifier weights, filter coefficients, and offsets, and there is also a method using logistic regression processing. If you want a machine to judge something, you have to teach the machine how to judge. In the present embodiment, a method of deriving image determination by machine learning is used. In addition, a rule-based method that applies rules acquired by humans through empirical rules and heuristics may be used.

Next, a method for determining constipation risk will be described using FIGS. 11 to 12E. In S7 and S11 of FIG. 2 and S63 of FIG. 6, the constipation risk is determined. Constipation risk can be inferred by generating the inference model shown in FIG. However, other than the method using this inference, it can be determined logically. The acquired information about the profile and lifestyle habits shown in FIG. 11 can be converted into a score, and the constipation risk can be determined based on this score.

Fig. 11 shows an overview of the logical constipation risk determination method. In determining the risk of constipation, the subject's profile/behavior, etc. for each item is converted into scores using the subject's profile collected in step S3 and the subject's lifestyle habits collected in step S5. do. First, items that can be used to determine constipation susceptibility, such as gender, age, and health condition, are collected from the subject's profile. In addition, from the subject's lifestyle habits, water intake, meat intake, regularity of life (determined from wake-up time, bedtime, etc.), amount of exercise (e.g., average number of steps), defecation tendency, etc. Collect items that can be used in determining ease of use.

The above items are examples, and may be added or omitted as appropriate. As for the detection method of these items, in addition to the questionnaire input in step S1, an AI speaker or the like placed in the subject's living place may be used, or a wearable sensor worn by the subject may be used. You may The wearable sensor can detect vibration, blood water content, pulse, blood pressure, body temperature, and the like of the subject. If there is vibration data and information related to blood flow of the subject, it is possible to obtain various kinds of information such as whether the subject is asleep or not, and whether the subject is exercising.

Next, using FIGS. 12A to 12E, an example of scoring the subject's profile and lifestyle habits and determining the risk of constipation based on these scores will be described. In the example described here, the constipation risk is determined using age, average number of steps per day, amount of water intake on day i, average sleep time for a predetermined period, and pulse for a predetermined period. Also, in this example, each item has 20 points, and the higher the risk, the higher the score. Therefore, when the total score of each item exceeds a predetermined number, it is determined that the risk of constipation is high.

The upper side of FIG. 12A is a graph showing the relationship between age and constipation, and the lower side of FIG. 12A is a chart showing scores for each age. As can be seen from the graph, the proportion of constipated people is low in men until they reach their 60s, but the proportion of constipated people in women is higher than that of men in their 20s. Therefore, as shown in the chart on the lower side of FIG. 12A, scores are given for each gender and age group. For example, from the profile information, if the subject belongs to a man in his 20s to 60s, 5 points are given as a score. A score of 10 is given.

The upper side of FIG. 12B is a graph showing the relationship between age and the average number of steps on day i, and the lower side of FIG. It is a chart showing giving. As can be seen from the graph, the average number of steps decreases in both men and women in their 60s. Here, points are given according to how many times the average number of steps per day of the subject is the average number of steps of the age group to which the subject belongs. For example, if the average number of steps per day of the subject is more than double the age group, 0 points are given, while the average number of steps per day of the subject is less than half of the age group. , 20 points are given.

The upper part of FIG. 12C is a graph showing the amount of water intake required on day i for each body weight, and the lower part of FIG. FIG. 11 is a chart showing scoring according to presence; FIG. As can be seen from the graph, as body weight increases so does the required water intake. Here, a score is given according to how many times the amount of water intake per day of the subject is the necessary intake amount for the body weight to which the subject belongs. For example, if the amount of water intake per day of the subject is more than double the required intake for the body weight, 0 points are given, while the amount of water intake per day for the subject is less than the required intake for the body weight. If the number of steps is less than half the amount, 20 points are awarded.

The upper side of FIG. 12D is a graph showing sleep hours (bedtime and wake-up times) of a certain subject for three days. It is desirable to always go to bed at the same time and always wake up at the same time, because constipation is generally less likely to occur when the rhythm of life is regular. Therefore, when assigning points based on sleep time, the time to go to bed and the time to wake up are compared with the usual time to go to bed and wake up. ing. An example of scoring is shown in the lower part of FIG. 20 points will be given if the time is 60 minutes or more compared to the normal time. It should be noted that stress may cause insomnia, so if sleep time is short, it may be advised to reduce stress. Insomnia occurs when a person does not fall asleep easily (pulse rate decreases) even though he/she has stopped activities such as standing and walking or sitting and shaking for a certain period of time.

The upper side of FIG. 12E is a graph showing changes in a subject's pulse for three days. When stressed, the sympathetic nerve becomes active and the pulse rate increases, while when the stress disappears, the parasympathetic nerve acts to decrease the pulse rate. Generally, when there is stress, it becomes easy to become constipated. The lower part of FIG. 12E shows an example of giving points. Here, the determination is based on a pulse rate of 100. FIG. In this example, if the pulse rate is rarely 100 or higher, a score of 0 is given, while if the pulse rate is consistently 100 or higher, a score of 20 is given.

As shown in FIGS. 12A to 12E, scores are given to subjects according to their age, average number of steps, water intake, regularity of sleep hours, and pulse rate. Since there are five items, if the total score (risk coefficient Frisk) of each item is 70 or more, it is determined that there is a risk of constipation. Further, as shown in the following formula (1), the risk Frisk may be calculated by weighting individual items.
Frisk=A.DB1+B.DB2+C.DB3+D.DB4+E.DB5 (1)
Here, A to E are weighting coefficients, and DB1 to DB5 are inspection items shown in FIGS. 12A to 12E.

In determining the risk of constipation, the value is not limited to the value calculated by the method described above. may Further, it is also possible to use variation in meal times, and make determination by increasing Frisk as variation increases. Furthermore, the amount of dietary fiber ingested is estimated from information such as food images before ingestion, purchase history, receipt information, etc., and the estimated dietary fiber intake is smaller than the recommended intake, the Frisk may be determined by increasing . If there is no problem even if the risk coefficient Frisk is high, a threshold value for determining that the subject is at risk may be set. Furthermore, an inference model may be generated by annotating the data shown in FIGS. 12A to 12E, adopting it as teacher data, and learning using this teacher data. Inference models and logical decisions may be used together

Next, the polyprisk determination method will be described with reference to FIGS. 13 and 14. FIG. In S7 and S11 of FIG. 2 and S63 of FIG. 6, the polyprisk is determined. It is also possible to generate the inference model shown in FIG. 8 and infer polyprisk. However, other than the method using this inference, it can be determined logically. Similarly to the constipation risk, the information obtained about the profile and lifestyle habits shown in FIG. 13 is converted into a score for the polyprisk, and the polyprisk can be determined based on this score.

Fig. 13 shows an overview of the logical polyprisk determination method. As for the polyprick risk, similarly to the determination of the constipation risk shown in FIG. The examiner's profile, behavior, etc. are converted into scores. First, from the subject's profile, sex, age, smoking habit (high risk if yes), drinking habit (high risk if yes), degree of obesity (linked to colorectal cancer risk), history of polyps (high risk if yes) Collect items that can be used for polyprisk determination.

As for the degree of obesity in the above items, as shown in Fig. 14, as BMI increases, polyplast risk also increases. BMI is a numerical value obtained by dividing body weight (kg) by the square of height (m), and represents the degree of obesity. Comparing the BMI value and the risk of colorectal cancer reveals that the higher the BMI value, the higher the risk of colorectal cancer. The solid line M indicates the risk for men, and the dashed line F indicates the risk for women. As can be seen from FIG. 14, the higher the BMI in men than in the women, the greater the risk of polyprisk.

In addition, in FIG. 13, considering the lifestyle habits of the subject, eating a lot of meat (can be determined from the content of meals), not exercising, defecation tendency (determined with particular emphasis on abnormal defecation), polyprisk judge. Although polyps are explained here, the same application is of course possible for other conditions requiring treatment such as tumors, ulcers, wounds, and bleeding.

The items listed for profile determination and lifestyle determination are converted into scores in the same manner as in FIGS. 12A to 12E, and the higher the score, the higher the polyprisk. In particular, when it is higher than a predetermined value, it is preferable to notify the subject of an urgent examination alert.

As described above, in each embodiment of the present invention, the examination risk when the subject undergoes an endoscopy is determined according to the information from the subject terminal (for example, see S11 in FIG. 1). , Based on the determination result of this examination risk, create chronological advice until the endoscopic examination, and transmit this chronological advice to the subject terminal (see, for example, S13). Therefore, since the advice is created based on the examination risk, it is possible to receive the advice necessary for appropriately undergoing an examination such as an endoscopy. In addition, in each embodiment of the present invention, it is a proposal aiming at a stress-free examination that does not interfere with daily life due to the examination taking time and labor, and a healthy body that does not need to be examined. It is also an idea to make it.

In each embodiment of the present invention, the service server 10 has been described as providing improvement advice to the subject when undergoing an endoscopy, but the service server provides services by a plurality of servers. Alternatively, it may be provided only within the user terminal 20 . In addition, although the explanation was mainly about undergoing endoscopic examination, various preparations and pretreatments are required not only for endoscopic examination but also for clinical examination. Embodiments can be applied. Even in barium examinations and X-ray examinations, accidents during pretreatment and examination, such as re-examination, may occur if the gas filled in the stomach leaks or there is a change in posture. , it is possible to apply each embodiment of the present invention with a similar concept.

In addition, in each embodiment of the present invention, logic-based determination was mainly explained, and determination was made by inference using machine learning in part. Either logic-based determination or inference-based determination may be appropriately selected and used in this embodiment. In addition, in the process of judgment, a hybrid judgment may be made by partially utilizing the merits of each.

Also, in each embodiment of the present invention, the control units 11, 21, 31, 36, and 41 have been described as devices configured from CPUs, memories, and the like. However, in addition to being configured as software by a CPU and a program, part or all of each part may be configured as a hardware circuit, and is described in Verilog, VHDL (Verilog Hardware Description Language), etc. A hardware configuration such as a gate circuit generated based on a program language may be used, or a hardware configuration using software such as a DSP (Digital Signal Processor) may be used. Of course, these may be combined as appropriate.

In addition, the control units 11, 21, 31, 36, and 41 are not limited to CPUs, and may be elements that function as controllers. may go. For example, each unit may be a processor configured as an electronic circuit, or may be each circuit unit in a processor configured with an integrated circuit such as an FPGA (Field Programmable Gate Array). Alternatively, a processor composed of one or more CPUs may read and execute a computer program recorded on a recording medium, thereby executing the function of each unit.

In each embodiment of the present invention, the service server 10 includes a control unit 11, a communication unit 12, a schedule management unit 13, a constipation/polyprisk determination unit 14, a risk reduction proposal unit 15, a hospital policy confirmation unit 16, a time It has been described as having the prediction unit 17 and the inspection result recording unit 18 . However, they do not need to be provided in an integrated device, and the above-described units may be distributed as long as they are connected by a communication network such as the Internet. Similarly, the user terminal 20 has been described as having the control section 21 , the communication section 22 , the clock section 23 , the lifestyle acquisition section 24 , and the UI section 25 . However, they do not need to be provided in an integrated device, and the above-described units may be distributed as long as they are connected by a communication network such as the Internet. The same applies to the hospital systems 30 and 35, the service server 40, and the like.

In addition, in recent years, artificial intelligence that can collectively determine various judgment criteria is often used, and improvements such as collectively performing each branch of the flow chart shown here are also within the scope of the present invention. It goes without saying that the If the user can input good or bad for such control, it is possible to learn the user's preference and customize the embodiment shown in the present application in a direction suitable for the user.

Furthermore, the constituent elements of different embodiments may be combined as appropriate. In particular, operations that use biological reactions, including voice recognition, require appropriate sensors, interfaces, and judgment circuits, but are not specifically described to avoid complication, but these manual operations by the user are substituted. It should be noted that the present invention can also be achieved by various possible improved techniques and alternative techniques.

In this specification, endoscopic examination was explained as an example, but it is also possible to apply not only to endoscopic examination but also to other clinical examinations and examinations involving medical practice. For example, X-ray examination of the stomach requires preparations such as dietary restrictions and administration of effervescent agents and barium for expanding the stomach. In addition, gas in the stomach flows back into the esophagus as a burp due to the tightness of the esophagus and the gastric junction, which reduces the degree of expansion of the stomach and the risk of not being able to take correct X-ray examination images. There is also a risk that the time from preparation to completion of the inspection will fluctuate. Each embodiment of the present invention can also be applied in such a case. All you have to do is book an examination and guide them to relax until the examination. Similarly, in other clinical examinations and examinations involving medical actions, there are many cases where physical and mental conditions change examination risks. It should be guided to improve the physical and mental condition so that the

In addition, among the techniques described in this specification, the control described mainly in the flowcharts can often be set by a program, and may be stored in a recording medium or recording unit. The method of recording in the recording medium and the recording unit may be recorded at the time of product shipment, using a distributed recording medium, or downloading via the Internet.

In addition, in one embodiment of the present invention, the operation in this embodiment was explained using a flowchart, but the order of the processing procedure may be changed, or any step may be omitted. Steps may be added, and specific processing contents within each step may be changed.

In addition, even if the operation flow in the claims, the specification, and the drawings is explained using words expressing the order such as "first" and "next" for convenience, in places not specifically explained, It does not mean that it is essential to carry out in this order.

The present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the spirit of the present invention at the implementation stage. Also, various inventions can be formed by appropriate combinations of the plurality of constituent elements disclosed in the above embodiments. For example, some components of all components shown in the embodiments may be deleted. Furthermore, components across different embodiments may be combined as appropriate.

10 Service server 11 Control unit 12 Communication unit 13 Schedule management unit 14 Constipation/polyprisk determination unit 15 Risk reduction proposal unit 16 Hospital policy confirmation unit 17 Time prediction unit 18 Inspection result recording unit 20 User terminal 21 Control unit 22 Communication unit 23 Clock unit 24 Lifestyle acquisition unit 25 UI unit 30 In-hospital system 31 Control unit 32 Schedule management unit 33 Communication unit 35 In-hospital system 36 Control unit 37 Schedule management unit 38 Communication unit 40 Service server 41 Control unit 42 Communication unit 43 ..Profile Management Department, 44..Situation Management Department, 45..Health Management Department, 46..Service Cooperation Department

Claims (13)

1. a risk determination unit that determines an examination risk when the subject undergoes an endoscopy according to information from the subject terminal;
   an advice creation unit that creates chronological advice until the endoscopic examination based on the determination result of the examination risk;
   a transmitting unit configured to transmit the chronological advice to the subject terminal;
   An examination guide service server characterized by comprising:
2. 　The examination guide service server according to claim 1, wherein the chronological advice is switched between a plurality of advices according to the target schedule and the examination risk.
3. 　The examination guide service server according to claim 1, wherein the chronological advice determines the effect of the chronological advice according to the improvement of the examination risk, and switches between a plurality of pieces of advice.
4. Having a risk reduction proposal unit that creates improvement advice to improve the inspection risk when the risk determination unit determines that the inspection risk is high when undergoing the inspection,
   2. The examination guide service server according to claim 1, wherein the advice unit includes the improvement advice when creating the chronological advice.
5. Equipped with a schedule proposal unit for proposing an inspection schedule,
   5. The examination guide service server according to claim 4, wherein the schedule proposal unit creates advice different from that before the examination risk is reduced in a state in which the examination risk of the subject is reduced.
6. The examination guide service server according to claim 5, wherein the schedule proposal unit proposes a period when the examination risk is reduced as the endoscopic examination examination period.
7. The examination guide service server according to claim 5, wherein the schedule proposal unit can selectively propose a plurality of candidates as the timing when the examination risk is reduced according to the situation of the examination facility.
8. The examination guide service server according to claim 1, wherein the risk determination unit determines the examination risk based on the subject's profile and lifestyle information.
9. The examination guide service server according to claim 1, wherein the examination risk is a risk that the time from preparation to completion of the endoscopic examination increases.
10. The examination guide service server according to claim 1, wherein the examination risk is at least one of cleaning risk and polyplast risk.
11. According to the information from the subject terminal, determine whether there is an examination risk when the subject undergoes clinical examination,
    Create chronological advice before the clinical test based on the test risk determination results,
    transmitting the chronological advice to the subject terminal;
    An inspection guide method characterized by:
12. a user information acquisition unit that acquires profile information and lifestyle information of a mobile terminal user;
    a judgment unit for judging correction points of lifestyle habits based on the lifestyle habit information in order to reduce restrictions that occur when undergoing a specific clinical examination in the future;
    a display unit that displays the correction points determined by the determination unit;
    A mobile terminal comprising:
13. Acquiring profile information and lifestyle information of mobile terminal users,
    In the future, in order to reduce the restrictions that occur when undergoing a specific clinical examination, determine points to correct lifestyle habits based on the lifestyle information,
    making it possible to communicate the determined corrections;
    A mobile terminal control method characterized by:

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