Information processing device, server device, computer program, and condition monitoring support method

Abstract

To improve the ability to understand the patient's condition. [Solution] The input interface 121 receives the patient's biological information. The processor 122 acquires contribution information corresponding to the contribution of N (N is 2 or more) first parameters to the patient's condition based on the biological information, and visualizes the contribution information on the visualization device 13 in a state in which at least M (M is 2 or more and less than or equal to N) first parameters included in the N first parameters are replaced with L (L is less than M) second parameters.

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus that processes biometric information of a patient. The present disclosure also relates to a server apparatus that is communicable with a client apparatus and includes the information processing apparatus. The present disclosure also relates to a computer program executable by a processor mounted on the information processing apparatus. The present disclosure also relates to a method for assisting in grasping the condition of a patient executed by at least one arithmetic unit.

Background Art

[0002] In clinical settings, scoring using multiple parameters is often performed to grasp the condition of a patient. Specifically, scores are defined based on the values and conditions of each parameter, and the condition of the patient is determined based on the total value of the scores of the multiple parameters. As such a scoring mechanism, EWS (Early Warning Score) designed for the purpose of early detection of deterioration of a patient's condition is known. Patent Document 1 discloses an apparatus that calculates and visualizes EWS based on a biological signal acquired from a patient.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a demand for enhancing the support for grasping the condition of a patient.

Means for Solving the Problems

[0005] One example of an aspect that the present disclosure can provide is an information processing apparatus, an interface that receives biometric information of a patient, A processor that acquires contribution information corresponding to the contribution of N (where N is 2 or more) first parameters to the patient's condition based on the aforementioned biological information, and visualizes the said contribution information in a visualization device in a state where at least M (where M is 2 or more and N or less) first parameters included in the N first parameters are replaced with L (where L is less than M) second parameters, It is equipped with.

[0006] One example of the embodiments that this disclosure may provide is a server device that is capable of communicating with a client device and is equipped with the above-mentioned information processing device, The interface receives the biometric information from the client device.

[0007] One example of the embodiments that this disclosure may provide is a computer program executable by a processor installed in an information processing device, By being executed, the information processing device will We accept the patient's biometric information. Based on the aforementioned biological information, contribution information corresponding to the contribution of N (where N is 2 or more) first parameters to the patient's condition is obtained. The contribution information is visualized by a visualization device in a state where at least M first parameters (where M is between 2 and N) included in the N first parameters are replaced with L second parameters (where L is less than M).

[0008] One example of the embodiments that this disclosure may provide is a method for assisting in the assessment of a patient's condition, which is performed by at least one computing device. We accept the patient's biometric information. Based on the aforementioned biological information, contribution information corresponding to the contribution of N (where N is 2 or more) first parameters to the patient's condition is obtained. The contribution information is visualized by a visualization device in a state where at least M first parameters (where M is between 2 and N) included in the N first parameters are replaced with L second parameters (where L is less than M). [Brief explanation of the drawing]

[0009] [Figure 1] This illustrates the configuration of a condition monitoring system according to one embodiment. [Figure 2] Figure 1 illustrates the functional configuration of the information processing device installed in the server device. [Figure 3] Figure 2 shows an example of the processing performed by the processor. [Figure 4] Figure 2 shows an example of contribution information visualized using the visualization device. [Figure 5] Figure 2 shows another example of contribution information visualized using the visualization device. [Figure 6] This figure illustrates the characteristic features related to the electrocardiogram waveform in Figure 5. [Figure 7] Figure 2 shows another example of contribution information visualized using the visualization device. [Modes for carrying out the invention]

[0010] An example of an embodiment will be described in detail with reference to the attached drawings.

[0011] Figure 1 illustrates the configuration of a condition monitoring system 10 according to one embodiment. The condition monitoring system 10 includes a client device 11 and a server device 12.

[0012] The client device 11 is a device for acquiring a patient's biological information. As used in this disclosure, the expression "device for acquiring a patient's biological information" encompasses both a device that directly receives signals corresponding to biological information from sensors attached to the patient and a device that ultimately receives data corresponding to biological information transmitted from such a device.

[0013] Therefore, there can be a plurality of client devices 11. Note that the same client device used by multiple users with different accounts can be regarded as multiple client devices. The client device 11 may be a stationary device installed at a specific location, or a portable device that can be carried by a user.

[0014] The server device 12 is installed at a location separated from the client device 11. The client device 11 and the server device 12 are configured to perform two-way communication of data via the communication network 20.

[0015] The client device 11 is configured to transmit the biological information data PH corresponding to the acquired biological information to the server device 12. The biological information data PH may be provided in the form of analog data or digital data according to the specifications of the communication network 20.

[0016] As illustrated in FIG. 2, the server device 12 includes an information processing device 120. The information processing device 120 includes an input interface 121, a processor 122, and an output interface 123. The processor 122 is an example of an arithmetic device.

[0017] The input interface 121 is configured as a hardware interface for receiving the biological information data PH transmitted from the client device 11. When the biological information data PH is provided in the form of analog data, the input interface 121 includes an appropriate conversion circuit including an A / D converter.

[0018] The processor 122 is configured to acquire contribution information CT corresponding to the contributions of a plurality of first parameters to the patient's condition based on the biological information data PH.

[0019] As an example, processor 122 performs processing corresponding to the task of inputting biometric information into the NEWS (National Early Warning Score) model. As illustrated in Figure 3, the NEWS model is configured to represent the state of multiple parameters that may contribute to the patient's condition with scores, and to obtain the sum of these scores as an index ID representing the condition. A higher sum corresponds to a higher degree of abnormality in the condition. A higher score for each parameter in the contributing information CT corresponds to a higher contribution to that abnormality.

[0020] Therefore, the biometric data PH in this example is configured to include, as an example of multiple primary parameters, information representing respiratory rate, oxygen saturation, presence or absence of supplemental oxygen therapy, systolic blood pressure, pulse rate, level of consciousness, and body temperature, which are referenced in the NEWS score.

[0021] The processor 122 is configured to replace at least some of the above-mentioned multiple first parameters with second parameters. In other words, the number of second parameters is less than the number of first parameters.

[0022] In this example, the three primary parameters, "respiratory rate," "oxygen saturation," and "presence or absence of supplemental oxygen therapy," are replaced by a secondary parameter called "respiratory function." The score for "respiratory function" is equal to the sum of the scores for "respiratory rate," "oxygen saturation," and "presence or absence of supplemental oxygen therapy."

[0023] Similarly, two primary parameters, including "systolic blood pressure" and "pulse rate," are replaced by a secondary parameter called "circulatory function." The score for "circulatory function" is equal to the sum of the scores for "systolic blood pressure" and "pulse rate." Furthermore, two primary parameters, including "level of consciousness" and "body temperature," are replaced by a secondary parameter called "other." The score for "other" is equal to the sum of the scores for "level of consciousness" and "body temperature."

[0024] In other words, the quantity corresponding to the total contribution does not change before and after the parameter substitution. As a result, the value of the total score, which is an indicator of the patient's condition, also does not change.

[0025] In other words, at least M (M is between 2 and N) elements in the N (N is 2 or greater) first parameters are replaced by L (L is less than M) second parameters. In this example, N=7, M=7, and L=3.

[0026] As illustrated in Figure 2, the condition monitoring system 10 includes a visualization device 13. The visualization device 13 is a device that visualizes an image containing predetermined information. The visualization device 13 can be implemented by a display that shows the image, a projector that projects the image, a printer that prints the image, and so on. The visualization device 13 may be part of the client device 11, or it may be a device independent of both the client device 11 and the server device 12.

[0027] The processor 122 is configured to output visualization data VS from the output interface 123, which causes the visualization device 13 to visualize contribution information CT in a state where at least a portion of the first parameter is replaced by the second parameter. Depending on the specifications of the visualization device 13, the visualization data VS may be provided in the form of analog data or in the form of digital data.

[0028] The output interface 123 is configured as a hardware interface capable of outputting visualization data VS. When the visualization data VS is provided in the form of analog data, the output interface 123 includes an appropriate conversion circuit, including a D / A converter.

[0029] Figure 4 illustrates the contribution information CT visualized by the visualization device 13. In this example, the total score "10," which is an index ID representing the patient's condition, is also visualized. In this example, the contribution of each of the multiple second parameters is visualized in the form of a pie chart.

[0030] Another example of a condition index acquisition model that represents the state of multiple parameters that may contribute to a patient's condition with scores and obtains the sum of these scores as an indicator of the condition is the SOFA (Sequential Organ Failure Assessment) model.

[0031] Referring to Figures 5 and 6, we will describe another example of a process in which at least some of the multiple first parameters are replaced by a smaller number of second parameters.

[0032] In this example, the processor 122 of the information processing device 120 is configured to input biological information data PH to an explainable artificial intelligence (hereinafter abbreviated as "explainable AI") that infers the patient's condition.

[0033] As illustrated in Figure 5, the explainable AI is configured to output an index ID representing the patient's condition as an inference result. In addition, the explainable AI is configured to visualize contribution information CT, which shows the extent to which each of the multiple parameters contributed to the inference result.

[0034] The indicator IDs for this example are defined to represent the patient's condition in three stages: "〇", "△", and "×". "〇" corresponds to a normal condition. "△" corresponds to a condition requiring attention. "×" corresponds to a condition requiring vigilance.

[0035] Therefore, the biometric data PH in this example is configured to include, as an example of multiple primary parameters, information representing heart rate, respiratory rate, oxygen saturation, blood pressure, and multiple features in the electrocardiogram waveform that are referenced or extracted by the explainable AI.

[0036] Figure 6 illustrates several features that are referenced or extracted in this example. Specifically, the RR interval, QRS width, and R wave height are the features that are referenced or extracted.

[0037] The explainable AI is implemented as an inference model trained through machine learning to output an index representing a patient's condition, along with information representing the contribution of each of the above-mentioned first parameters, when biometric information containing the above-mentioned multiple first parameters is input.

[0038] In this example as well, the processor 122 is configured to replace at least some of the above-mentioned multiple first parameters with second parameters. In other words, at least M (M is between 2 and N) of the N (N is 2 or more) first parameters are replaced with L (L is less than M) second parameters. In this example, N=7, M=3, and L=1.

[0039] Specifically, three first parameters, including "RR interval," "QRS width," and "R wave height," are replaced by a second parameter called "ECG waveform." The amount representing the contribution of "ECG waveform" is equal to the sum of the amounts representing the individual contributions of "RR interval," "QRS width," and "R wave height." In other words, the amount corresponding to the total contribution does not change before and after the parameter replacement. As a result, the indicators showing the patient's condition also do not change.

[0040] By obtaining information on the contribution of each of several primary parameters to a patient's condition, it may be possible to infer the impact on changes in the condition. While an increase in the number of primary parameters allows for more detailed inferences about which parameters influenced the condition, it also becomes more difficult to identify the parameter related to the problem at a glance. According to the configuration of this embodiment, at least some of the multiple primary parameters included in the contribution information CT are replaced with a smaller number of secondary parameters, thereby reducing the number of parameters presented in the list. Therefore, even if the number of primary parameters increases to enable more detailed inferences about changes in the patient's condition, the difficulty in identifying the parameter related to the problem can be suppressed. As a result, the ability to support understanding the patient's condition can be improved.

[0041] In this embodiment, the processor 122 of the information processing device 120 changes the name of the second parameter used for visualization by the visualization device 13 to a different name that encompasses the names of the M first parameters.

[0042] In the example illustrated with reference to Figure 3, the name of the second parameter, "respiratory function," encompasses the names of the three first parameters: "respiratory rate," "oxygen saturation," and "presence or absence of supplemental oxygen therapy." This substitution is based on the fact that each of "respiratory rate," "oxygen saturation," and "presence or absence of supplemental oxygen therapy" is a parameter related to "respiratory function."

[0043] Similarly, the name of the second parameter, "circulatory function," encompasses the names of the two first parameters, "systolic blood pressure" and "pulse rate." The name of the second parameter, "other," encompasses the names of the two first parameters, "level of consciousness" and "body temperature."

[0044] In the example explained with reference to Figure 5, the name of the second parameter, "ECG waveform," encompasses the names of the three first parameters: "RR interval," "QRS width," and "R wave height." This substitution is based on the fact that each of "RR interval," "QRS width," and "R wave height" is a parameter related to the features of the "ECG waveform."

[0045] This configuration allows for an intuitive understanding of the contributions of multiple first parameters before they are replaced by the second parameter, while suppressing the increase in the area occupied by the visualization of the name of the second parameter within the area where contribution information can be visualized.

[0046] Alternatively, the name of the second parameter may be determined as a name that lists the names of the multiple first parameters before replacement. For example, the name of the second parameter "Other" in the example explained with reference to Figure 3 could be determined as "Level of Consciousness / Body Temperature". This configuration facilitates understanding which first parameter was replaced by the second parameter.

[0047] The name of the second parameter, which is in the form of listing multiple first parameter names, can also be said to encompass the names of multiple first parameters. Therefore, the expression "another name that encompasses the names of the first parameters" used in this disclosure for the second parameter means a name of the second parameter that does not directly include the names of the first parameters, while assuming the user's understanding of the relationship between the first and second parameters.

[0048] Several approaches are possible regarding how to determine the multiple first parameters that will be used to replace the second parameter.

[0049] For example, several primary parameters that can be included in a secondary parameter, which has a relatively high probability of causing events that contribute to the patient's condition, may be subject to replacement. For instance, patients undergoing hospitalization are more prone to aspiration due to muscle weakness. As a result, "respiratory function" is often impaired due to complications such as pneumonia. Alternatively, in patients after surgery or with sepsis, shock symptoms often occur due to a decrease in circulating blood volume caused by the inflammatory response. This can lead to an overall impact on "circulatory function," such as a drop in blood pressure and a compensatory increase in heart rate.

[0050] Therefore, in the example explained with reference to Figure 3, the first parameters, "respiratory rate," "oxygen saturation," and "presence or absence of supplemental oxygen therapy," which can be included in the second parameter, "respiratory function," are preferentially selected as targets for replacement.

[0051] By replacing multiple primary parameters with secondary parameters that have a relatively high probability of causing events that contribute to the patient's condition, the number of parameters presented to the user can be reduced, thereby improving the overall clarity of the situation. In addition, since there is little need to consider "which parameter has the highest contribution" among such multiple primary parameters, it becomes easier to pay attention to the contribution of the remaining primary parameters.

[0052] As an alternative example, several first parameters that can be included in a second parameter, which has a relatively low probability of occurring, may be subject to replacement.

[0053] In the example explained with reference to Figure 3, by grouping the second parameter, which has a relatively low probability of occurring as an event contributing to the patient's condition, under "Other," the first parameters that can be included in this second parameter, namely "Level of Consciousness" and "Body Temperature," are preferentially selected as targets for replacement.

[0054] By replacing multiple primary parameters with secondary parameters that have a relatively higher probability of causing events that contribute to the patient's condition, the number of parameters presented to the user can be reduced, thereby improving the overall clarity of the situation. In addition, since there is less need to pay attention to the contributions of such multiple primary parameters, it becomes easier to focus attention on parameters that have a greater contribution to the patient's condition.

[0055] In the example explained with reference to Figure 5, the "RR interval," "QRS width," and "R wave height" as primary parameters, which are observation units not typically observed in clinical practice, are preferentially selected as replacements for the "electrocardiogram waveform," which is an observation unit of so-called "vital signs."

[0056] The determination of the multiple first parameters to be replaced is performed by the processor 122 of the information processing device 120. The determination may be made in advance, or it may be made dynamically according to the contribution of each first parameter in the contribution information CT acquired in response to the input of biological information data PH. In either case, information defining the combination of the multiple first parameters to be replaced and a single second parameter is stored in storage (not shown) in advance so that the processor 122 can refer to it.

[0057] As illustrated in Figure 7, the processor 122 of the information processing device 120 can visualize an indicator MK that indicates the visualized parameter is a second parameter resulting from a substitution.

[0058] The visualization method can be determined as appropriate, provided that it is distinguishable from the first parameter that is not being replaced. In addition to or in place of the indicator MK, the color, size, font, background color, background pattern, etc., can be changed as appropriate. In the visualization example shown in Figure 4, a distinguishable visualization method is applied to the graph region representing the contribution of each second parameter.

[0059] In this case, the user of the client device 11 can input an instruction to select the image of the visualized sign MK through an appropriate user interface. As illustrated in Figure 2, the input interface 121 of the information processing device 120 can receive instruction information IS corresponding to the instruction from the client device 11.

[0060] The processor 122 may be configured to cause the visualization device 13 to visualize a plurality of first parameters before they are replaced by the selected indicator MK, in addition to the second parameter associated with the selected indicator MK, in response to instruction information IS received by the input interface 121.

[0061] In this example, the label MK associated with the "ECG waveform" as the second parameter is selected. Therefore, the multiple first parameters, "RR interval," "QRS width," and "R wave height," which were previously replaced by the "ECG waveform," are additionally visualized.

[0062] In addition, instead of the second parameter associated with the selected label MK, multiple first parameters that were previously replaced by the second parameter may be visualized.

[0063] When the input interface 121 receives instruction information IS corresponding to the instruction to deselect the indicator MK, the processor 122 returns the second parameter to its original visualization state.

[0064] With this configuration, information related to the contributions of multiple first parameters, which have been omitted from visualization by replacing them with the second parameter, can be checked at any time, thus achieving both the ability to view and access contribution information.

[0065] The processor 122 of the information processing device 120, which has various functions as exemplified above, can be realized by at least one general-purpose microprocessor operating in cooperation with at least one general-purpose memory. Examples of general-purpose microprocessors include CPUs, MPUs, and GPUs. Examples of general-purpose memory include ROMs and RAMs. In this case, the ROM may store computer programs that implement the various functions described above. ROM is an example of a non-temporary computer-readable medium that stores computer programs. The general-purpose microprocessor selects at least a portion of the program stored in the ROM and loads it onto the RAM, and then executes the above-described processes in cooperation with the RAM. The computer program may be pre-installed in the general-purpose memory, or it may be downloaded from an external server device via a communication network and then installed in the general-purpose memory. In this case, the external server device is an example of a non-temporary computer-readable medium that stores computer programs.

[0066] The processor 122 may be implemented by at least one dedicated integrated circuit capable of executing the above-described computer program. Examples of dedicated integrated circuits include microcontrollers, ASICs, FPGAs, etc. In this case, the above-described computer program is pre-installed in a memory element included in the dedicated integrated circuit. This memory element is an example of a computer-readable medium that stores the computer program. The processor 122 can also be implemented by a combination of a general-purpose microprocessor and a dedicated integrated circuit.

[0067] The various configurations described herein are merely examples to facilitate understanding of this disclosure. Each example configuration may be modified or combined with others as appropriate within the scope of the intent of this disclosure.

[0068] In the above embodiment, a specific first parameter is replaced by a single second parameter. However, a specific first parameter may be used to replace multiple second parameters, provided that the amount corresponding to the total contribution does not change before and after the replacement. For example, "oxygen saturation" as the first parameter in Figure 3 may be involved in both "respiratory function" and "circulatory function" as second parameters.

[0069] In this case, the proportion of the contribution of "oxygen saturation" that is replaced by "respiratory function" and the proportion that is replaced by "circulatory function" may be defined, or the contributions of "respiratory function" and "circulatory function" may overlap. In the latter case, for example, a visualization method may be adopted that makes the overlap clear in the graph exemplified in Figure 4.

[0070] In the above embodiment, as illustrated in Figures 4 and 5, the indicator ID representing the patient's condition is visualized along with the contributing information CT. However, visualization of the indicator ID is not essential.

[0071] If contribution information CT corresponding to the contribution of multiple primary parameters to the patient's condition can be obtained, then the biological information data PH does not necessarily need to be input into a condition index acquisition model that involves obtaining an index ID.

[0072] In the above embodiment, the information processing device 120 is mounted on a server device 12 that can communicate with the client device 11 via a communication network 20. However, the information processing device 120 may be mounted on any suitable device capable of acquiring biological information data PH. The information processing device 120 may be mounted on the client device 11, or it may be mounted on a device such as a biological information monitor that directly receives signals corresponding to biological information from sensors attached to the patient.

[0073] The processes of acquiring contribution information CT, replacing multiple first parameters with a single second parameter, and visualizing the second parameter on the visualization device 13 do not necessarily need to be performed on the same device. A configuration in which these processes are shared between the client device 11 and the server device 12 can also be adopted.

[0074] The configurations listed below also constitute part of this disclosure. Item 1: An interface for receiving patient biometric information, A processor that acquires contribution information corresponding to the contribution of N (where N is 2 or more) first parameters to the patient's condition based on the aforementioned biological information, and visualizes the said contribution information in a visualization device in a state where at least M (where M is 2 or more and N or less) first parameters included in the N first parameters are replaced with L (where L is less than M) second parameters, It is equipped with Information processing device. Item 2: The processor makes the name of the second parameter visible to the visualization device as a separate name that encompasses the names of the M first parameters. The information processing device described in item 1. Item 3: The aforementioned biological information is input into a condition index acquisition model that acquires an index representing the patient's condition based on the contribution of each of the N first parameters. An information processing device as described in item 1 or 2. Item 4: The condition indicator acquisition model is implemented by an explainable artificial intelligence trained through machine learning to output the contributing information based on the input of the biological information. The information processing device described in item 3. Item 5: The M first parameters are associated with a plurality of features that the explainable artificial intelligence extracts from the biometric information for inference. The information processing device described in item 4. Item 6: The processor causes the indicator, along with the L second parameters, to be visualized in the visualization device. An information processing device as described in any one of items 3 to 5. Item 7: The processor determines the M first parameters, which are a plurality of first parameters that can be included in the second parameter, the second parameter which has a relatively high probability of an event contributing to the patient's condition occurring. An information processing device as described in any one of items 1 through 6. Item 8: The processor determines the M first parameters, which are a plurality of first parameters that can be included in the second parameter, the second parameter having a relatively low probability of an event contributing to the patient's condition occurring. An information processing device as described in any one of items 1 through 7. Item 9: When the interface receives information corresponding to the user's instructions, the processor causes the visualization device to visualize the M first parameters in addition to or instead of the L second parameters. An information processing device as described in any one of items 1 through 8. Item 10: A server device that can communicate with a client device and is equipped with an information processing device as described in any one of items 1 to 9, The interface receives the biometric information from the client device. Server device. [Explanation of Symbols]

[0075] 11: Client device, 12: Server device, 120: Information processing device, 121: Input interface, 122: Processor, 13: Visualization device, CT: Contributing information, IS: Indication information, PH: Biological information data

Claims

1. An interface for receiving patient biometric information, A processor that acquires contribution information corresponding to the contribution of N (where N is 2 or more) first parameters to the patient's condition based on the aforementioned biological information, and visualizes the said contribution information in a visualization device in a state where at least M (where M is 2 or more and N or less) first parameters included in the N first parameters are replaced with L (where L is less than M) second parameters, It is equipped with Information processing device.

2. The processor makes the name of the second parameter visible to the visualization device as a separate name that encompasses the names of the M first parameters. The information processing apparatus according to claim 1.

3. The aforementioned biological information is input into a condition index acquisition model that acquires an index representing the patient's condition based on the contribution of each of the N first parameters. The information processing apparatus according to claim 1.

4. The condition indicator acquisition model is implemented by an explainable artificial intelligence trained through machine learning to output the contributing information based on the input of the biological information. The information processing apparatus according to claim 3.

5. The M first parameters are associated with a plurality of features that the explainable artificial intelligence extracts from the biometric information for inference. The information processing apparatus according to claim 4.

6. The processor causes the indicator, along with the L second parameters, to be visualized in the visualization device. The information processing apparatus according to claim 3.

7. The processor determines the M first parameters, which are a plurality of first parameters that can be included in the second parameter, the second parameter which has a relatively high probability of an event contributing to the patient's condition occurring. The information processing apparatus according to claim 1.

8. The processor determines the M first parameters, which are a plurality of first parameters that can be included in the second parameter, the second parameter having a relatively low probability of an event contributing to the patient's condition occurring. The information processing apparatus according to claim 1.

9. When the interface receives information corresponding to the user's instructions, the processor causes the visualization device to visualize the M first parameters in addition to or instead of the L second parameters. The information processing apparatus according to claim 1.

10. A server device that can communicate with a client device and is equipped with an information processing device according to any one of claims 1 to 9, The interface receives the biometric information from the client device. Server device.

11. A computer program that can be executed by a processor installed in an information processing device, By being executed, the information processing device will We accept the patient's biometric information. Based on the aforementioned biological information, contribution information corresponding to the contribution of N (where N is 2 or more) first parameters to the patient's condition is obtained. The contribution information is visualized by a visualization device in a state where at least M (where M is between 2 and N) first parameters included in the N first parameters are replaced by L (where L is less than M) second parameters. Computer program.

12. A method for assisting in the assessment of a patient's condition, which is performed by at least one computing device, We accept the patient's biometric information. Based on the aforementioned biological information, contribution information corresponding to the contribution of N (where N is 2 or more) first parameters to the patient's condition is obtained. The contribution information is visualized by a visualization device in a state where at least M (where M is between 2 and N) first parameters included in the N first parameters are replaced by L (where L is less than M) second parameters. Methods for supporting the assessment of a patient's condition.

Images