Disease diagnosis device, disease diagnosis program, and computer-readable recording medium

Abstract

To provide a disease determination device, a disease determination program and a computer-readable recording medium which can determine a disease with higher accuracy.SOLUTION: A disease determination device for determining a disease in an object person on the basis of a state value being a value of a state item being at least one of a vital item and an inspection item comprises: a storage unit 41 which stores a transition following the time course of the state value or a transition following the time course of a processing value being a value of processing the state value for each state item for each of a plurality of diseases; an input unit 42 which inputs information about at least one state value for the individual object person; and a disease determination unit 43 which determines the disease of the object person on the basis of the input information about the state value and the transition stored in the storage unit 41. The disease determination unit 43 calculates a variable component of the state value or processing value on the basis of the input state value, and determines the disease of the object person on the basis of whether or not the variable component matches the transition stored in the storage unit 41.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a disease diagnosis device, a disease diagnosis program, and a computer-readable recording medium. [Background technology]

[0002] Conventionally, a disease diagnosis device has been proposed that determines whether a subject is ill based on vital values ​​such as the subject's body temperature and blood oxygen concentration, and test values ​​obtained through tests such as blood tests and liver function tests (see, for example, Patent Document 1). This device determines whether a subject is ill based on vital values, detected values, their average values, and the amount of change therein. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-131495 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the device described in Patent Document 1 lacks accuracy in determining illness because it determines illness based on the value itself, the average value, and the amount of change.

[0005] The present invention has been made to solve these conventional problems, and its purpose is to provide a disease diagnosis device, a disease diagnosis program, and a computer-readable recording medium that are capable of diagnosing diseases with higher accuracy. [Means for solving the problem]

[0006] The disease diagnosis device of the present invention is a disease diagnosis device that determines a disease occurring in a subject based on a status value, which is the value of a status item that is at least one of a vital item and a test item, and is equipped with a memory means that stores, for each status item for each of a plurality of diseases, the change in the status value over time, or the change in a processed value, which is a value obtained by processing the status value, over time; an input means that inputs information on at least one status value for an individual subject; and a judgment means that judges the subject's disease based on the status value information input by the input means and the change stored in the memory means, and the judgment means calculates the change component of the status value or the processed value based on the status value input by the input means, and judges the subject's disease based on whether the change component matches the change component stored in the memory means.

[0007] It should be noted that the determination of disease here is not limited to the case of identifying a single disease, but also includes the case of narrowing down to multiple diseases that may be present.

[0008] In addition, the disease diagnosis program of the present invention is a disease diagnosis program for causing a computer to function as the above-mentioned disease diagnosis device, and the computer-readable recording medium of the present invention is a computer-readable recording medium on which the above-mentioned disease diagnosis program is recorded. [Effects of the Invention]

[0009] According to the present invention, for each of a plurality of diseases, the transition of the state value or processed value over time for each state item is stored, the change component of at least one state value or processed value for the individual subject is calculated, and the disease of the subject is diagnosed based on whether the calculated change component matches the transition. Here, depending on the disease, a specific state value may reach a certain value or above a certain value over a long period of time after the onset of disease symptoms, or may reach a certain value or above a certain value rapidly in a short period of time. Therefore, simply referring to the state value or average value makes it difficult to determine the disease. In particular, even if a certain value is reached rapidly over a short period of time, the change component varies slightly for each disease. Therefore, by storing the transition for each disease and determining whether it matches the change component, the disease can be diagnosed more accurately. Therefore, the disease can be diagnosed with higher accuracy. [Brief explanation of the drawings]

[0010] [Figure 1] 1A and 1B are diagrams showing the configuration of a disease assessment device according to an embodiment of the present invention, in which (a) is an external view and (b) is a block diagram. [Figure 2] 1 is a software configuration diagram showing a CPU of a disease determination device according to an embodiment of the present invention. [Figure 3] 3 is a first graph showing an example of a transition stored in the storage unit shown in FIG. 2; [Figure 4] 3 is a second graph showing an example of a transition stored in the storage unit shown in FIG. 2. [Figure 5] 10 is a third graph showing an example of a transition stored in the storage unit shown in FIG. 2. [Figure 6] 1 is a flowchart showing a disease determination method according to the present embodiment. [Figure 7] FIG. 10 is a software configuration diagram showing the CPU of the disease assessment device according to the second embodiment. [Figure 8] 8 is a diagram for explaining processing by an elapsed time calculation unit shown in FIG. 7. FIG. [Figure 9] 10 is a flowchart showing a disease determination method according to a second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] The present invention will be described below in accordance with preferred embodiments. Note that the present invention is not limited to the embodiments shown below and can be modified as appropriate without departing from the spirit of the present invention. In addition, in the embodiments shown below, some components are omitted from illustration and description, but it goes without saying that publicly known or well-known technologies are applied as appropriate to the details of the omitted technologies within the scope of the content described below.

[0012] FIG. 1 is a configuration diagram showing a disease assessment device according to an embodiment of the present invention, where (a) shows an external view and (b) shows a block diagram.

[0013] 1(a) and 1(b) is realized as a function of a personal computer, for example, and determines the disease of a subject (e.g., a patient) based on information input by an operator. Such a disease determination device 1 is provided with operation means such as a keyboard 2 and a mouse 3, and determines the disease through operations on the operation means.

[0014] Such a disease assessment device 1 includes a CPU (Central Processing Unit) 4, a display 5, a communication I / F (interface) section 6, and an HDD (Hard Disk Drive) 7 in addition to an operation means.

[0015] The CPU 4 controls the entire disease diagnosis apparatus 1 according to this embodiment, and includes a ROM (Read Only Memory) 4a and a RAM (Random Access Memory) 4b. The ROM 4a is a read-only memory that stores a disease diagnosis program for operating the disease diagnosis apparatus 1. The RAM 4b is a readable and writable memory that stores various data and has an area required for the processing operations of the CPU 4.

[0016] The display 5 displays images input by operating the keyboard 2 or mouse 3, and displays diseases diagnosed by the disease diagnosis device 1. The communication I / F unit 6 is an interface for communicating with other devices. The contents stored in a memory unit (reference numeral 41) described later and the contents input to an input unit (reference numeral 42) described later may be acquired from other devices through this communication I / F unit 6.

[0017] The HDD 7 is an auxiliary storage device connected to a personal computer. Similar to the ROM 4a, this HDD 7 may store a disease diagnosis program for causing the disease diagnosis apparatus 1 to function. That is, the CPU 4 may be configured to realize each function of the disease diagnosis apparatus 1 according to the present embodiment in accordance with the program stored in the HDD 7. Furthermore, if possible, a USB (Universal Serial Bus) or the like may be provided instead of or in addition to the HDD.

[0018] In the following description, it is assumed that the disease determination device 1 is used in a medical institution, but the disease determination device 1 may also be used in other organizations such as local governments and fire departments. Furthermore, if applicable, the disease determination device 1 may also be used in other locations. Furthermore, in this embodiment, the disease determination device 1 is described as a function of a personal computer, but the disease determination device 1 is not limited to this, and may also be configured by a system consisting of a mobile terminal such as a smartphone and a server, or a system consisting of two or more personal computers.

[0019] Fig. 2 is a software configuration diagram showing the CPU 4 of the disease determination device 1 according to the embodiment of the present invention. As shown in Fig. 2, the CPU 4 includes a storage unit (storage means) 41, and executes a disease determination program, causing an input unit (input means) 42, a disease determination unit (determination means) 43, and a display control unit 44 to function.

[0020] The storage unit 41 stores, for each of a plurality of diseases, the transition of the status value over time for each status item, or the transition of the processed value, which is a value obtained by processing the status value, over time. In this embodiment, the status item refers to at least one of a vital sign item and a test item.

[0021] Vital items are items that can be output as numerical values ​​by contacting a sensor with the body or by attaching a measuring instrument or device, and examples of these include body temperature, blood pressure, and blood oxygen concentration.

[0022] Test items are those in which a part of the human body (blood, urine, etc.) is collected and quantified using methods stipulated by the JSCC Standardization Act, etc., or those in which physical functions are quantified by a doctor, nurse, etc. operating equipment or by a doctor or nurse, etc. assisting the subject in using the equipment. Test items include, for example, vital capacity, γ-GT, uric acid, C-reactive protein (CRP), white blood cell count (WBC), urinary occult blood, and hearing level.

[0023] Furthermore, a status value refers to the value of a status item. For example, for a status item (vital item) called body temperature, the status value would be a numerical value such as 36.5°C. Similarly, for a status item (vital item) called blood oxygen concentration, the status value would be a numerical value such as 98%. Furthermore, for a status item (test item) called CRP, the status value would be a numerical value such as 0.10 mg / dL.

[0024] The storage unit 41 stores the transitions of such status values ​​over time, or the transitions of processed values ​​obtained by processing the status values ​​over time, for each disease and for each status item. The transitions stored in the storage unit 41 represent the transitions when no treatment is being performed.

[0025] Figures 3 to 5 are graphs showing examples of transitions stored in the storage unit 41 shown in Figure 2. Note that although Figures 3 to 5 illustrate diseases limited to pneumothorax, asthma, and pneumonia, transitions are not limited to these three diseases, and transitions are also stored for various other diseases.

[0026] As shown in Figure 3, pneumothorax, asthma, and pneumonia are all lung-related diseases that tend to result in a decrease in blood oxygen concentration. In the example shown in Figure 3, for all three diseases, the blood oxygen concentration decreases to X% (e.g., 85-90%). However, there are significant differences in the speed at which it reaches X%. First, with pneumothorax, a hole forms in the lung, and the blood oxygen concentration tends to decrease rapidly from the moment the hole opens. Furthermore, with asthma, the blood oxygen concentration tends to decrease to X% over a period of approximately 6 to 12 hours after the onset of symptoms. Furthermore, with pneumonia, the blood oxygen concentration tends to decrease to X% over a period of approximately 48 to 72 hours after the onset of symptoms.

[0027] As shown in FIG. 3, the storage unit 41 stores, for the status item of blood oxygen concentration, the transition of the status value over time for each disease (for example, pneumothorax, asthma, and pneumonia).

[0028] As shown in Figure 4, pneumothorax, asthma, and pneumonia are all lung diseases, and heart rate also tends to increase. Specifically, with pneumothorax, heart rate tends to increase rapidly and to a high value from the time a hole opens in the lung. With asthma, heart rate tends to gradually increase from about 6 to 12 hours after symptoms begin to appear, eventually reaching an increase rate of, for example, about 20%. With pneumonia, heart rate tends to gradually increase from about 48 to 72 hours after symptoms begin to appear, eventually reaching a higher increase rate than with asthma.

[0029] As shown in Fig. 4, the storage unit 41 stores, for each disease (e.g., pneumothorax, asthma, and pneumonia), a time-dependent change in a processed value (heart rate increase rate) obtained by processing a status value (heart rate value) for the status item of heart rate. It goes without saying that, in order to calculate the heart rate increase rate, information on the normal heart rate is required in advance. The normal heart rate in this case may be reported by the subject himself / herself, or may be information read out from a second storage unit 45 of the disease assessment device 1, which corresponds to the second storage unit 45 of the second embodiment described later.

[0030] Furthermore, as shown in Figure 5, pneumothorax, asthma, and pneumonia are all lung diseases, but only pneumonia is an infectious disease. For this reason, the white blood cell count tends to maintain the initial value (standard value) in cases of pneumothorax and asthma. In contrast, in cases of pneumonia, the WBC count gradually increases approximately 48 to 72 hours after the onset of symptoms, and eventually tends to reach an obviously abnormal value.

[0031] As shown in FIG. 5, the storage unit 41 stores, for the status item WBC, the transition of the status value over time for each disease (for example, pneumothorax, asthma, and pneumonia).

[0032] As described above, the storage unit 41 stores the transition of the status value or the transition of the processed value for each status item for each disease.

[0033] Referring again to Figure 2, as shown in Figure 2, the input unit 42 inputs information on at least one status value for an individual subject, and in particular in this embodiment, two or more sets of information for one status item are input, each set consisting of information on a status value after the onset of a disease and time information indicating the time (date and time) when the status value was obtained. The input unit 42 inputs the set information via an operating means, or inputs set information stored in a memory area of ​​its own device or another device, etc.

[0034] The disease determination unit 43 determines the disease of the subject based on the state values ​​input by the input unit 42, and is equipped with a candidate determination unit 43a, a change component calculation unit 43b, and a transition fitting unit 43c.

[0035] The candidate determination unit 43a determines a candidate disease based on at least one state value input by the input unit 42. For example, if the WBC shown in FIG. 5 is within the reference value, an infectious disease such as pneumonia can be ruled out. Also, as shown in FIG. 3, if the blood oxygen concentration drops to, for example, around X%, there is a possibility of a pulmonary disease. In this way, the candidate determination unit 43a determines a candidate disease based on the state value input by the input unit 42.

[0036] Here, because the status value is a value at a certain point in time, there is a limit to narrowing down the disease from the status value alone. For example, referring to the blood oxygen concentration in Figure 3, the blood oxygen concentration drops to around X% in all of pneumothorax, asthma, and pneumonia. Therefore, if the status value obtained by attaching a blood oxygen concentration sensor to a subject is X%, it is not possible to identify whether it is pneumothorax, asthma, or pneumonia.

[0037] Therefore, the disease diagnosis device 1 according to this embodiment further narrows down the diseases by using the functions of the change component calculation unit 43b and the transition fitting unit 43c. The change component calculation unit 43b calculates the change component of the state value or the processed value based on the state value information input by the input unit 42. Here, the change component can be, for example, 1) a change rate and time, 2) a change amount and time, or 3) a change rate only, which indicates a change in the state value or the processed value having a concept of time. The change component calculation unit 43b can calculate, for example, the time of 1) from the difference in time information included in two sets of information. Furthermore, the change rate of 1) can be calculated, for example, from the difference in time information included in two sets of information and the difference in state value information included in the two sets of information. 2) and 3) can be calculated in a similar manner. Below, the change component will be described using 1) as an example. Furthermore, the following description will be given assuming that two sets of information related to the state items of blood oxygen concentration and heart rate are input.

[0038] The transition fitting unit 43c determines the disease of the subject based on whether the change component calculated by the change component calculation unit 43b matches the transition stored in the storage unit 41. In particular, the transition fitting unit 43c performs fitting only on diseases determined as candidates by the candidate determination unit 43a. The processing of the transition fitting unit 43c will be described with reference to Figs. 3 and 4.

[0039] First, it is assumed that the change component calculation unit 43b calculates a time ΔT3 and a rate of change ΔB based on the set information of the blood oxygen concentration input by the input unit 42. The transition fitting unit 43c determines whether there is a portion of the stored transition of the blood oxygen concentration where the time ΔT3 and the rate of change ΔB match.

[0040] 3, for the progression of asthma and pneumonia, there is a portion where the time ΔT3 (t1 to t2 for asthma, t3 to t4 for pneumonia) and the rate of change ΔB match, while for the progression of pneumothorax, there is no portion where the time ΔT3 and the rate of change ΔB match. Based on these results, the disease determination unit 43 can determine that the subject does not have pneumothorax.

[0041] Furthermore, it is assumed that the change component calculation unit 43b calculates a time ΔT4 and a rate of change ΔH based on the set information of the heart rate input by the input unit 42. The transition fitting unit 43c determines whether there is a portion in the stored transition of the heart rate increase rate where the time ΔT4 and the rate of change ΔH match.

[0042] 4, the transition of asthma has a portion where the time ΔT4 (t1 to t2) and the rate of change ΔH match. On the other hand, the transition of pneumothorax and pneumonia has no portion where the time ΔT4 and the rate of change ΔH match. In such a case, the disease determination unit 43 can determine that the subject does not have pneumothorax or pneumonia.

[0043] 4, there is a portion where the time ΔT4 and the rate of change ΔH coincide during the period from time t5 to time t6 in the progression of pneumonia. However, if the measurement time of the state value of the blood oxygen concentration and the measurement time of the state value of the heart rate are approximately the same, a contradiction arises because the elapsed time between the two (the time elapsed since the onset of symptoms) is significantly different.

[0044] To give a specific example, suppose the blood oxygen concentration and heart rate status values ​​are obtained around noon on January 1, 2019. Next, suppose the blood oxygen concentration and heart rate status values ​​are obtained around 3:00 PM on January 1, 2019. In this case, for the blood oxygen concentration, as shown in Figure 3, the period t1-t2, which is between 6 and 12 hours elapsed, corresponds to asthma, and the period t3-t4, which is between 48 and 72 hours elapsed, corresponds to pneumonia. On the other hand, for the heart rate change, as shown in Figure 4, the period t1-t2, which is between 6 and 12 hours elapsed, corresponds to asthma, and the period t5-t6, which clearly exceeds 72 hours elapsed, corresponds to pneumonia. Here, for pneumonia, the elapsed time for the blood oxygen concentration is between 6 and 12 hours, while the elapsed time for the heart rate change clearly exceeds 72 hours. In other words, there are differences in the elapsed time for each status item for the same disease.

[0045] Therefore, when the transition fitting unit 43c fits the transition of one status item of a specific disease and finds that the change component matches at a specific elapsed time, it is preferable to set a forbidden region for fitting based on the specific elapsed time when fitting the transition of another status item of the specific disease. In the above example, since asthma matches the blood oxygen concentration at an elapsed time of around 48 hours to 72 hours, for example, the forbidden region for the heart rate change is set to be outside the range of elapsed time of 24 hours (48 hours - a predetermined value) to 96 hours (72 hours + a predetermined value). This makes it possible to prevent fitting to inconsistent transitions and reduce the processing load.

[0046] Furthermore, when the transition fitting unit 43c performs fitting on the transition of the blood oxygen concentration as shown in Fig. 3 and there is an inconsistent transition such as pneumothorax, it is preferable not to perform fitting on the inconsistent transition such as pneumothorax for the transition of the heart rate increase rate (another status item) shown in Fig. 4. In other words, it is preferable that the transition fitting unit 43c excludes diseases whose change components do not match after fitting to the transition of a specific status item when fitting to the transition of other status items.

[0047] As described above, the disease determination unit 43 determines the subject's disease based on the fitting result by the transition fitting unit 43c. In the above example, since there are only three diseases, pneumothorax, asthma, and pneumonia, the subject's disease can be identified as pneumonia by fitting to the transitions of blood oxygen concentration and heart rate increase rate. However, since many status items and transitions of many diseases are actually stored, the disease determination unit 43 may not ultimately be able to identify a single disease. In such cases, the disease determination unit 43 determines that the subject may be suffering from multiple narrowed-down diseases.

[0048] Information on the disease determined by the disease determination unit 43 is displayed on the display 5, printed, etc. Furthermore, information on the determined disease may be transmitted to another device or the subject's mobile terminal.

[0049] Next, a disease determination method using the disease determination device 1 according to this embodiment will be described. FIG. 6 is a flowchart showing the disease determination method according to this embodiment. As shown in FIG. 6, first, the input unit 42 inputs a plurality of sets of information (S1). In this process, the input unit 42 inputs a plurality of sets of information after the patient has contracted a disease. Whether or not the patient has contracted a disease may be determined by a doctor's judgment, or the patient may be determined to have contracted a disease at the time of visiting a hospital or the like, and a plurality of sets of information based on tests or the like after the patient visit may be input.

[0050] Next, the candidate determining unit 43a determines candidate diseases from the state values ​​of the latest set information (S2). In this process, the candidate determining unit 43a determines candidates by, for example, excluding diseases that cannot have the state values ​​indicated by the set information.

[0051] Thereafter, the change component calculation unit 43b calculates the change component based on the multiple sets of information input in step S1 (S3). In this process, it is preferable that the change component is calculated for each of two or more condition items. In this embodiment, since disease candidates are determined and narrowed down to a certain extent in step S2, it is possible that a single disease can be identified by obtaining one change component for one condition item. However, in order to more reliably narrow down to one disease, it is preferable to obtain multiple change components for multiple condition items.

[0052] Next, the transition fitting unit 43c fits the change component calculated in step S3 to the candidate transition calculated in step S2 (S4). In this process, as described above, if a certain status item does not match the transition of a certain disease, fitting of the disease to other status items is prohibited, and if they match, a prohibited area is set based on the elapsed time.

[0053] Thereafter, the disease determination unit 43 determines whether one disease has been identified (S5). If it is determined that one disease has been identified (S5: YES), the disease determination unit 43 determines the progression of the disease (S6). In this case, the disease determination unit 43 determines the progression based on the elapsed time when the transition matches. For example, in the transition of pneumonia shown in FIG. 3, the blood oxygen concentration drops to its lowest point when the elapsed time is around 48 hours to 72 hours. Therefore, if the current elapsed time is 6 hours, for example, the disease determination unit 43 calculates the progression as 6 hours / 48 hours and 6 hours / 72 hours, and determines the progression to be 8.3% to 12.5%.

[0054] Next, the display control unit 44 displays the fact that the subject is suffering from the identified disease and the degree of progression (S7), after which the processing shown in FIG.

[0055] On the other hand, if it is determined that the disease has not been identified (S5: NO), that is, if there is a possibility that the patient is suffering from multiple diseases, the display control unit 44 displays that the patient is suffering from one of the multiple diseases (disease candidate) (S8). Thereafter, the processing shown in Fig. 6 ends. If possible, the progress of all disease candidate may be calculated and displayed.

[0056] In this manner, the disease diagnosis device 1, disease diagnosis method, disease diagnosis program, and computer-readable recording medium according to this embodiment store the time-dependent transition of state values ​​for each state item for each of a plurality of diseases, calculate the change component of at least one state value for each individual subject, and determine the subject's disease based on whether the calculated change component matches the transition. Depending on the disease, a specific state value may reach a certain value or higher long after the onset of disease symptoms, or may reach a certain value or higher rapidly in a short period of time. Therefore, simply referencing the state value or average value makes it difficult to determine the disease. In particular, even if a certain value is reached rapidly in a short period of time, the change component varies slightly for each disease. Therefore, by storing the transition for each disease and determining whether the change component matches, disease can be diagnosed with greater accuracy. Therefore, disease can be diagnosed with greater accuracy.

[0057] Furthermore, for the same status item, two or more sets of information, each containing information on the status value after the onset of the disease and time information indicating the time when the status value information was obtained, are input, and the change component of the status value or processed value is calculated based on the two or more sets of information, so that, for example, by performing two tests on the same status item after a patient is hospitalized, it is possible to calculate the rate of change in the disease onset state, etc. In particular, when the rate of change in the status value is calculated from the status value obtained when the patient is normal and the status value obtained after hospitalization, it is unclear at what point the patient became ill and symptoms began to appear, and the change component may be inaccurate. However, because the change component is calculated based on two or more sets of information containing the status value after the onset of the disease and time information, an accurate change component can be calculated, and the disease can be identified with higher precision.

[0058] Furthermore, a disease candidate is determined based on at least one state value, and the disease is identified based on a change component of at least one state value or processed value calculated for the progression of the determined disease candidate. Therefore, for example, by narrowing down the candidates to a certain extent based on state values ​​such as body temperature, blood oxygen concentration, CRP (C-reactive protein), etc., and then using the change component, further narrowing down the candidates can be performed by applying the change component after narrowing down to a certain extent. Therefore, disease diagnosis based on the change component can be performed while utilizing disease diagnosis based on existing state values.

[0059] Furthermore, because a disease is determined based on the change components of the status values ​​or processed values ​​of two or more status items, it is possible to determine cases where the change components of one status value or processed value match for a certain disease, but the change components of other status values ​​or processed values ​​do not match, etc. This makes it possible to determine the relationship between two or more status items, and further narrow down the diseases using the change components.

[0060] Furthermore, if a disease of the subject is determined, the degree of progression of the disease is determined. Here, the stored transition indicates a state equivalent to the degree of progression in the absence of any treatment, so if the change component matches the transition, it becomes possible to determine the current degree of progression. Therefore, it is possible to determine not only the disease but also the degree of progression.

[0061] Next, a second embodiment of the present invention will be described. The disease determination device according to the second embodiment is similar to that according to the first embodiment, but some configurations and processing contents are different. The differences from the first embodiment will be described below.

[0062] 7 is a software configuration diagram showing the CPU 4 of the disease determination device 1 according to the second embodiment. First, in the second embodiment, the CPU 4 includes a second storage unit (second storage means) 45. The second storage unit 45 stores normal values, which are the values ​​of status items previously acquired for an individual subject when the individual subject is normal. That is, the second storage unit 45 stores, as normal values, status values ​​when the individual subject is not affected by a disease, such as a blood oxygen concentration of 100%, a heart rate of ○○○, and a WBC reference value.

[0063] Furthermore, the disease determination unit 43 according to the second embodiment may input multiple sets of information for one status item, as in the first embodiment, or may input information on one status value for disease determination. Normally, if only status value information for one status item is input, it becomes impossible to calculate the times ΔT3 and ΔT4 shown in Figures 3 and 4 from the difference in time information. This causes problems in calculating the change components.

[0064] Therefore, the disease determination unit 43 according to the second embodiment includes an elapsed time calculation unit (calculation means) 43d. The elapsed time calculation unit 43d calculates the elapsed time from the time when the information on the state value input by the input unit 42 is obtained.

[0065] The elapsed time calculation unit 43d calculates the elapsed time, for example, as follows: Figure 8 is a diagram for explaining the processing by the elapsed time calculation unit 43d shown in Figure 7. In Figure 8, the vertical axis represents the white blood cell count (WBC) and C-reactive protein (CRP), and the horizontal axis represents the elapsed time.

[0066] When a subject suffers from an infectious disease, the white blood cell count tends to increase in order to eliminate foreign substances such as bacteria and viruses that have entered the body, and for example, the white blood cell count reaches α at elapsed time Tα1. Thereafter, the white blood cell count reaches a maximum at elapsed time Tmax, and then, as a result of the smooth elimination of foreign substances, the white blood cell count reaches α again at elapsed time Tα2. Thereafter, the white blood cell count gradually decreases.

[0067] On the other hand, C-reactive protein is a protein that increases in the blood in pathological conditions involving inflammation or tissue necrosis. This C-reactive protein tends to reach its maximum value later than the white blood cell count, showing β1 at time Tα1 and β2 (>β1) at time Tα2.

[0068] Based on the above trends, for example, when a subject suffers from an infectious disease, a certain amount of elapsed time can be calculated from the white blood cell count and C-reactive protein values. For example, if the white blood cell count is α and the C-reactive protein is β2, the elapsed time calculation unit 43d can calculate the elapsed time to be Tα2. Therefore, by also testing the white blood cell count and C-reactive protein when information on the status values ​​is obtained, the elapsed time calculation unit 43d can calculate the elapsed time at the time the information on the status values ​​was obtained. Note that this tendency is not limited to infectious diseases, but also applies to trauma, tumors, etc.

[0069] Because the disease determining unit 43 includes the elapsed time calculating unit 43d, the change component calculating unit 43b can calculate the change component based on the elapsed time calculated by the elapsed time calculating unit 43d, the normal value, and the information on the state value. This allows the change component to be calculated based on information on at least one state value, and after the calculation, disease determination can be performed in the same way as in the first embodiment.

[0070] Fig. 9 is a flowchart showing a disease determination method according to the second embodiment. As shown in Fig. 9, first, the input unit 42 inputs set information (S11). The information input here is assumed to be one set information for one status item, but multiple sets of information may be input. Furthermore, instead of being limited to one set information, only one status value information may be input for one status item.

[0071] Next, the input unit 42 inputs normal values ​​of the status items corresponding to the set information input in step S11 (S12). Thereafter, the elapsed time calculation unit 43d calculates the elapsed time (S13). At this time, the white blood cell count and C-reactive protein values ​​are input to the disease diagnosis device 1, and the elapsed time calculation unit 43d calculates the elapsed time based on these values ​​as described with reference to FIG.

[0072] Next, the change component calculation unit 43b calculates the change component of the state value based on the set information (state value information) input in step S11, the normal value input in step S12, and the elapsed time calculated in step S13 (S14).

[0073] Thereafter, the transition fitting unit 43c performs fitting to the transition (S15) in the same manner as in step S4 shown in Fig. 6. Note that in this process, similarly to the first embodiment, if a certain status item does not match the transition of a certain disease, fitting of the disease with other status items is prohibited, and if a match occurs, a prohibited area is set based on the elapsed time.

[0074] Thereafter, in the processing of steps S16 to S19, the same processing as steps S5 to S8 shown in FIG. 6 is performed, and the processing shown in FIG. 9 ends.

[0075] In this way, the disease determination device 1, disease determination method, disease determination program, and computer-readable recording medium according to the second embodiment can provide the same effects as those of the first embodiment.

[0076] Furthermore, according to the second embodiment, normal values ​​acquired during normal times are stored, and the time elapsed since the onset of disease symptoms is calculated. Here, when calculating the change component of the state value or processed value from the normal value obtained when the patient was normal and the state value obtained after hospitalization, etc., it is unclear at what point the patient became ill and symptoms began to appear, and the change component may be inaccurate. However, by calculating the time elapsed since the onset of disease symptoms, an accurate change component can be calculated, and the disease can be identified with higher accuracy.

[0077] The present invention has been described above based on the embodiments, but the present invention is not limited to the above embodiments, and modifications may be made or known or well-known technologies may be combined within the scope of the spirit of the present invention.

[0078] For example, in the above embodiment, the disease diagnosis program is stored in the ROM 4a of the disease diagnosis apparatus 1, but this is not limiting and the program may be stored in other types of recording media such as a USB, CD-ROM, or CD-R.

[0079] Additionally, in the above embodiment, the disease assessment device 1 is assumed to be a single device, but the present invention is not limited to this and may be a system formed by a plurality of devices.

[0080] Furthermore, the disease determination device 1 may be customized based on the condition value (normal value) of an individual subject. For example, the initial value (normal value) of the blood oxygen concentration has been described as 100%, but depending on the subject, the initial value may be 97%, and the transition may be shifted in parallel by 3% along the vertical axis.

[0081] In this embodiment, when inputting the set information, the input unit 42 may receive continuous information from a sensor such as a thermometer attached to the subject. [Explanation of symbols]

[0082] 1: Disease determination device 41: Storage unit (storage means) 42: Input unit (input means) 43: Disease judgment department (judgment means) 43a: Candidate judgment section 43b: Change component calculation unit 43c: Transition fitting section 43d: Elapsed time calculation unit (calculation means) 44: Display control section 45:Second storage unit (second storage means)

Claims

1. A disease determination device that determines a disease occurring in a subject based on a status value that is a value of a status item that is at least one of a vital item and a test item, a storage means for storing, for each of a plurality of condition items for each of a plurality of diseases, a transition of a condition value over time or a transition of a processed value obtained by processing the condition value over time; an input means for inputting information on at least one status value for each of two or more status items for an individual subject; a determination means for determining a disease of a subject based on information on the state values ​​of two or more state items input by the input means and the transition stored in the storage means, the determination means calculates a change component of the state value or the processed value based on the state values ​​of two or more state items input by the input means, and determines a disease of the subject based on whether the change component matches the transition stored in the storage means; The storage means stores transitions of a plurality of status items of a specific disease with respect to the elapsed time from a common start point set in advance. A disease diagnosis device characterized by:

2. the input means inputs, for one status item, two or more sets of information each including information on the status value after the onset of a disease and time information indicating the time when the information on the status value was obtained; The determining means calculates a change component of the state value or the processed value based on two or more sets of information input by the input means.

2. The disease diagnosis device according to claim 1.

3. A disease determination device that determines a disease occurring in a subject based on a status value that is a value of a status item that is at least one of a vital item and a test item, a storage means for storing, for each of a plurality of diseases, a transition of a status value over time or a transition of a processed value obtained by processing the status value over time for each status item; an input means for inputting information on at least one status value for an individual subject; a determining means for determining a disease of a subject based on the information of the state value input by the input means and the transition stored in the storage means; A second storage means for storing normal values, which are values ​​of status items previously acquired for an individual subject under normal conditions; and a calculation means for calculating the time elapsed since the onset of symptoms of the disease based on the white blood cell count and C-reactive protein value of the individual subject, The determination means calculates a change component of a state value or a processed value based on the state value input by the input means, and determines whether the state value or the processed value has a disease based on whether the change component matches the transition stored by the storage means. The determination means calculates the change component of the state value or the processed value based on the normal value stored in the second storage means for the same state item, the state value input by the input means, and the elapsed time calculated by the calculation means. A disease diagnosis device characterized by:

4. The determining means determines a disease candidate based on at least one of the state values ​​input by the input means, and identifies the disease based on a change component of at least one of the state values ​​or processed values ​​calculated with respect to the transition of the determined disease candidate.

4. The disease diagnosis device according to claim 1, wherein the disease diagnosis device is a device for determining whether or not a disease has occurred.

5. The determining means calculates a change component of the status value or processed value for each of two or more status items, and determines a disease based on each calculated change component.

4. The disease diagnosis device according to claim 3.

6. A disease diagnosis program for causing a computer to function as the disease diagnosis device according to any one of claims 1 to 5.

7. A computer-readable recording medium on which the disease diagnosis program according to claim 6 is recorded.

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