A pediatric tumor management system based on diet and psychological intervention

Abstract

The present invention relates to the field of medical health management, and in particular to a pediatric tumor management system based on diet and psychological intervention, including a data acquisition module, a label setting module, a node setting module and an interaction setting module; the data acquisition module is used to obtain the tumor staging results of the monitoring target; the label setting module is used to set at least one target auxiliary treatment label based on the tumor staging results, and the target auxiliary treatment label is a measure dimension label for auxiliary monitoring of the target tumor treatment; the node setting module is used to set at least one implementation node according to the implementation frequency of the target auxiliary treatment label, and the implementation node is a time node for implementing auxiliary treatment measures; the interaction setting module is used to set an interaction window based on the interactive object of the target auxiliary treatment label, and the interaction window is used to visualize the implementation node to the interactive object, and the auxiliary treatment measures corresponding to the implementation node. The present invention can provide a personalized auxiliary treatment plan for the rehabilitation process of children's tumor treatment.

Description

Technical Field

[0001] The present invention relates to the field of medical health management, and in particular to a children's tumor management system based on diet and psychological intervention. Background Art

[0002] As a disease that seriously affects children's health and quality of life, the treatment and management of childhood tumors have always been the focus of medical attention. Traditional treatment methods often focus on surgery, chemotherapy and radiotherapy, while ignoring the important role of diet and psychological intervention in the treatment of childhood tumors. In recent years, with the deepening of medical research, people have gradually realized that diet and psychological state have a significant impact on the recovery of tumor patients. Good eating habits can provide necessary nutritional support and enhance the patient's physical fitness and immunity; and a positive psychological state can help patients better cope with the stress and challenges during treatment.

[0003] At present, because children are in a critical period of growth and development, their dietary and psychological needs are different from those of adults, and they need more detailed and personalized intervention measures. Therefore, there is an urgent need for a pediatric tumor management system based on diet and psychological intervention, which aims to provide personalized diet and psychological intervention programs for pediatric tumor patients through scientific methods, in order to achieve better treatment effects and quality of life. Summary of the invention

[0004] In view of the deficiencies of existing technologies and practical application needs, the present invention provides a pediatric tumor management system based on diet and psychological intervention, which aims to support the rehabilitation process of pediatric tumor treatment in multiple dimensions, thereby improving the treatment effect and promoting the rehabilitation of the monitored targets.

[0005] The pediatric tumor management system based on diet and psychological intervention provided by the present invention includes a data acquisition module, a label setting module, a node setting module and an interaction setting module; wherein the data acquisition module is used to obtain the tumor staging result of the monitored target, and the tumor staging result is a quantitative assessment result of the tumor development status; the label setting module is used to set at least one target auxiliary treatment label based on the tumor staging result, and the target auxiliary treatment label is a measure dimension label for auxiliary monitoring of the target tumor treatment; the node setting module is used to set at least one implementation node according to the implementation frequency of the target auxiliary treatment label, and the implementation node is a time node for implementing auxiliary treatment measures; the interaction setting module is used to set an interaction window based on the interaction object of the target auxiliary treatment label, and the interaction window is used to visualize the implementation node and the auxiliary treatment measures corresponding to the implementation node to the interaction object, and to obtain feedback information of the interaction object based on the auxiliary treatment measures.

[0006] The benefits of the pediatric tumor management system based on diet and psychological intervention provided by the present invention are as follows: the pediatric tumor management system based on diet and psychological intervention provided by the present invention sets multiple auxiliary treatment target auxiliary treatment labels according to the tumor staging results of the monitoring target, so as to comprehensively cover the auxiliary treatment dimensions required by the monitoring target in the tumor treatment process, thereby supporting the treatment and rehabilitation process of the monitoring target in multiple dimensions, thereby improving the treatment effect and promoting the rehabilitation of the monitoring target; and the present invention can also generate corresponding implementation nodes according to the implementation frequency of different auxiliary treatment labels, and recommend auxiliary treatment measures to relevant personnel in a timely manner through the interactive window, which is conducive to the stable implementation of auxiliary treatment measures; at the same time, the present invention can also use the interactive window to collect feedback information from the monitoring target or medical staff, which is conducive to further optimizing the auxiliary treatment plan. Compared with the traditional tumor management system that focuses on primary treatment, the present invention realizes the personalized recommendation and implementation effect evaluation of auxiliary treatment measures through the interaction between multiple functional modules, significantly expands the attention to auxiliary treatment, and enables the tumor monitoring target to obtain targeted auxiliary treatment measure recommendations during the rehabilitation process, which not only conforms to the trend of personalized medicine, but also helps to improve the overall treatment effect.

[0007] Optionally, the pediatric tumor management system based on diet and psychological intervention is connected to an electronic medical record system that stores the medical records of the monitored target, and the step of obtaining the tumor staging result of the monitored target includes the following steps: obtaining the identity information of the monitored target, and extracting the tumor staging result of the monitored target from the electronic medical record system based on the identity information. The present invention realizes the automatic acquisition of the tumor staging result of the monitored target by connecting to the electronic medical record system, avoiding errors and delays caused by manual input.

[0008] Optionally, the setting of at least one target auxiliary therapy label based on the tumor staging result includes the following steps: using the tumor staging result to obtain the state index of the monitored target; based on the state index, obtaining the demand index of the monitored target for different auxiliary therapy labels; based on the demand index of the monitored target for different auxiliary therapy labels, selecting at least one target auxiliary therapy label from different auxiliary therapy labels. The present invention can accurately evaluate the demand of the monitored target for different auxiliary therapy labels according to the specific state index of the monitored target, and then can intelligently select the target auxiliary therapy label that best meets the current state of the monitored target from a variety of auxiliary therapy labels, to ensure the personalization and pertinence of the auxiliary therapy.

[0009] Optionally, the use of the tumor staging result to obtain the state indicator of the monitoring target includes the following steps: obtaining a first state indicator based on the tumor type in the tumor staging result; obtaining a second state indicator based on the tumor size in the tumor staging result; obtaining a third state indicator based on the lymph node invasion in the tumor staging result; and obtaining a fourth state indicator based on the tumor metastasis in the tumor staging result. The present invention provides a basis for accurately evaluating the health status of the monitoring target by refining the tumor staging results, and helps to formulate a more accurate auxiliary treatment plan for each state indicator.

[0010] Optionally, the auxiliary treatment label includes a dietary intervention label and a psychological intervention label. The present invention introduces multiple dimensional auxiliary treatment labels, which helps each monitoring target to obtain comprehensive and accurate auxiliary treatment measure recommendations.

[0011] Optionally, obtaining the demand index of the monitoring target for different auxiliary treatment labels based on the state index comprises the following steps: respectively obtaining the influence parameters of different auxiliary treatment labels on the state index; and respectively obtaining the demand index of different auxiliary treatment labels based on the influence parameters of different auxiliary treatment labels. The demand index of any auxiliary treatment label satisfies the following calculation model: , where j represents the number of the adjuvant therapy label, represents the monitoring target's demand index for the jth auxiliary treatment label, i represents the number of the status indicator, Indicates the number of status indicators, represents the i-th state indicator influence parameter of the j-th auxiliary treatment label, The present invention quantifies the influence of different auxiliary treatment labels on the state indicators of the monitoring target, thereby realizing the accurate assessment of the monitoring target's needs for different auxiliary treatments, which helps to more scientifically select auxiliary treatment labels, thereby ensuring the personalization and accuracy of the treatment plan, and effectively improving the treatment effect and rehabilitation quality of the monitoring target.

[0012] Optionally, the acquisition of the influence parameters of different auxiliary treatment labels on the state indicators, the influence parameters of any auxiliary treatment label on the state indicators, includes the following acquisition steps: acquiring a sample data set, any sample in the sample data set is an effect score of an auxiliary treatment measure corresponding to an auxiliary treatment label on a group of state indicators; using the sample data set, fitting the influence parameters of the auxiliary treatment label on each state indicator in the effect scoring model, so that the difference between the predicted effect score and the actual effect score of all samples by the effect scoring model is minimized. The present invention quantifies the influence of the auxiliary treatment label based on the actual sample data, ensures that the selection of the auxiliary treatment label is more in line with the actual situation, and contributes to the effective implementation of the auxiliary treatment measures.

[0013] Optionally, the effect scoring model is: ,in, represents the predicted effect score of the jth adjuvant therapy label, represents the first state indicator influencing parameter of the j-th auxiliary treatment label, represents the first state indicator, represents the second state indicator impact parameter of the j-th auxiliary treatment label, represents the second state indicator, represents the nth state indicator influencing parameter of the jth auxiliary treatment label, Represents the nth state indicator. The effect scoring model provided by the present invention provides a basis for fitting the influencing parameters of various auxiliary treatment labels.

[0014] Optionally, the objective function of the effect scoring model fitting is: , + + ,in, To minimize the objective function, represents the number of samples, g represents the sample number, represents the g-th sample, represents the predicted effect score of the j-th adjuvant treatment label corresponding to the g-th sample, It represents the first state indicator influence parameter of the jth auxiliary treatment label corresponding to the gth sample, represents the first state indicator corresponding to the g-th sample, Indicates the second state indicator influence parameter of the jth auxiliary treatment label corresponding to the gth sample, represents the second state indicator corresponding to the g-th sample, represents the nth state indicator influence parameter of the jth auxiliary treatment label corresponding to the gth sample, represents the nth state index corresponding to the gth sample. The objective function provided by the present invention provides a basis for fitting the influencing parameters of various auxiliary treatment labels.

[0015] Optionally, the step of selecting at least one target auxiliary therapy label from different auxiliary therapy labels based on the monitoring target's demand index for different auxiliary therapy labels includes the following steps: obtaining a demand index threshold based on the tumor staging result; selecting at least one target auxiliary therapy label from different auxiliary therapy labels according to a selection rule based on the demand index threshold, wherein the selection rule includes the following: if there is an auxiliary therapy label whose demand index is greater than or equal to the demand index threshold, one or more auxiliary therapy labels whose demand index is greater than or equal to the demand index threshold are set as the target auxiliary therapy label; if there is no auxiliary therapy label whose demand index is greater than or equal to the demand index threshold, the auxiliary therapy label with the largest demand index is set as the target auxiliary therapy label. The present invention can ensure that when the demand index is low, the monitoring target can still obtain the highest priority auxiliary therapy measure recommendation, thereby improving the accuracy and effectiveness of personalized treatment, and helping to improve the overall rehabilitation effect of the monitoring target. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of the children's tumor management system based on diet and psychological intervention provided by the present invention;

[0017] Figure 2 This is a flow chart of the method for managing childhood tumors based on diet and psychological intervention provided by the present invention. DETAILED DESCRIPTION

[0018] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0019] In one embodiment, see Figure 1 , Figure 1 This is a schematic diagram of the children's tumor management system based on diet and psychological intervention provided by the present invention.

[0020] like Figure 1 As shown, the children's tumor management system based on diet and psychological intervention provided by the present invention includes a data collection module, a label setting module, a node setting module and an interaction setting module.

[0021] The data acquisition module is used to obtain the tumor staging result of the monitored target, and the tumor staging result is a quantitative evaluation result of the tumor development status.

[0022] Further, the data acquisition module is connected to the label setting module and the node setting module respectively; further, in order to improve the execution efficiency of the children's tumor management system based on diet and psychological intervention, as Figure 1 As shown, the data acquisition module is also connected to an electronic medical record system that stores the medical records of the monitored target.

[0023] Among them, the label setting module is used to set at least one target auxiliary treatment label based on the tumor staging result, and the target auxiliary treatment label is a measure dimension label for assisting in monitoring the treatment of the target tumor.

[0024] Furthermore, the label setting module is connected to the node setting module and the interaction setting module to ensure that the target-assisted treatment label can be accurately converted into an implementation node, and is connected to the interaction setting module so that the auxiliary measures corresponding to the target-assisted treatment label can be visually displayed in the interaction window.

[0025] Among them, the node setting module is used to set at least one implementation node according to the implementation frequency of the target auxiliary treatment tag, and the implementation node is a time node for implementing auxiliary treatment measures.

[0026] Furthermore, the node setting module is respectively connected to the node setting module and the interaction module to ensure that the information of each target auxiliary treatment label can be displayed in the interactive interface, which helps the auxiliary measures corresponding to each target auxiliary treatment label to be implemented at the appropriate time.

[0027] Among them, the interaction setting module is used to set an interaction window based on the interactive object of the target auxiliary treatment label, and the interaction window is used to visualize the implementation node and the auxiliary treatment measures corresponding to the implementation node to the interactive object, and to obtain feedback information of the interactive object based on the auxiliary treatment measures.

[0028] Furthermore, the interaction setting module is also connected to the label setting module and the node setting module respectively to transmit the user's feedback information back to the label setting module and the node setting module, so that the system can make real-time adjustments according to the actual treatment effect and user needs, thereby improving the accuracy and effectiveness of personalized treatment.

[0029] Furthermore, the pediatric tumor management system based on diet and psychological intervention is applicable to Figure 2 The dietary and psychological interventions for the management of childhood cancers are shown in Figure 2 This is a flow chart of the method for managing childhood tumors based on diet and psychological intervention provided by the present invention.

[0030] like Figure 2As shown, the method for managing childhood tumors based on diet and psychological intervention includes the following steps:

[0031] S01. The data acquisition module obtains a tumor staging result of a monitored target, where the tumor staging result is a quantitative evaluation result of a tumor development status.

[0032] The monitoring target described in the present invention refers to the object monitored and managed by the system, specifically, a child tumor patient who is receiving tumor management and treatment.

[0033] It is understandable that the tumor staging results described in the present invention are quantitative evaluation results of monitoring the development status of the target tumor based on a specific staging system, such as the TNM tumor staging system, the Wilm tumor staging system or the neuroblastoma staging system.

[0034] In this embodiment, the tumor staging result obtained in step S01 is a quantitative evaluation result of the development status of the monitored target tumor based on the TNM tumor staging system, wherein the specific staging rules of the TNM tumor staging system are existing technologies and are not described in detail here.

[0035] It can be known that the TNM tumor staging system includes three core indicators: T (Tumor, tumor size), N (Nodes, lymph node invasion) and M (Metastasis, tumor metastasis); among them, T includes TX, T0, Tis, T1, T2, T3 and T4, 7 status indicators, N includes NX, N0, N1, N2 and N3, 5 status indicators, M includes M0 and M1, 2 status indicators. Therefore, the tumor staging results obtained by the present invention include tumor type and the above three core indicators.

[0036] In one or some other embodiments, obtaining the tumor staging result of the monitored target in step S01 can be obtained by asking the medical staff of the monitored target, checking the paper or electronic medical records of the monitored target, etc.; and then inputting the tumor staging result into the processor through the input device of the children's tumor management system based on diet and psychological intervention for subsequent data processing.

[0037] To improve the efficiency of the implementation of childhood cancer management methods based on diet and psychological interventions, such as Figure 1 As shown, the pediatric tumor management system based on diet and psychological intervention is connected to the electronic medical record system storing the medical records of the monitoring target. Further, the tumor staging result of the monitoring target described in step S01 includes the following steps:

[0038] S011. Obtain the identity information of the monitored target.

[0039] It can be understood that the identity information is the identity identifier of the monitoring target, which is used to extract the tumor staging result of the monitoring target from the electronic medical record system.

[0040] Furthermore, the identity information may be a medical record number, ID number, medical insurance number, social security number or other identifiable code. It is understandable that the identity information may be recorded in text form, or in other forms such as RFID tags, QR codes, bar codes, etc.

[0041] Therefore, the medical record number, ID number, medical insurance number or social security number of the monitored target can be directly input into the pediatric tumor management system based on diet and psychological intervention through the input device, or the QR code of the monitored target can be scanned through the input device.

[0042] S012. Extracting the tumor staging result of the monitored target from the electronic medical record system according to the identity information.

[0043] Furthermore, the relevant protocol between the children's tumor management system based on diet and psychological intervention and the electronic medical record system uses the identity information of the monitored target as a retrieval condition, and the children's tumor management system based on diet and psychological intervention sends a data query request to the electronic medical record system. The electronic medical record system then queries the corresponding content in the internal database based on the data query request, and returns the data query result to the children's tumor management system based on diet and psychological intervention, wherein the data query result includes the identity information of the monitored target and the tumor staging result based on the identity information.

[0044] S02. The label setting module sets at least one target auxiliary treatment label based on the tumor staging result, and the target auxiliary treatment label is a measure dimension label for assisting in monitoring the treatment of the target tumor.

[0045] In this embodiment, the step S02 of setting at least one target auxiliary treatment tag based on the tumor staging result includes the following steps:

[0046] S021. Utilize the tumor staging results to obtain status indicators of the monitored target.

[0047] Furthermore, based on the tumor staging results of the TNM tumor staging system, the status indicators of the monitoring target can be obtained through the following steps:

[0048] S0211. Obtain a first status indicator based on the tumor type in the tumor staging result.

[0049] If the tumor staging result of a child monitoring target is displayed as "osteosarcoma, T3N2M1", the first status indicator of the monitoring target is osteosarcoma.

[0050] S0212. Obtain a second status indicator based on the tumor size in the tumor staging result.

[0051] Based on the tumor staging result "osteosarcoma, T3N2M1" in the above example, the second status indicator of the monitoring target is T3, which means that the tumor is large in size and has invaded deep tissues or surrounding organs.

[0052] S0213. Obtain a third status indicator based on the lymph node invasion status in the tumor staging results.

[0053] Based on the tumor staging result "osteosarcoma, T3N2M1" in the above example, the third status indicator of the monitoring target is N2, which means that the tumor has metastasized to a distant lymph node area.

[0054] S0214. Obtain a fourth status indicator based on the tumor metastasis status in the tumor staging result.

[0055] Based on the tumor staging result "osteosarcoma, T3N2M1" in the above example, the fourth status indicator of the monitoring target is M1, which indicates that the tumor has distant metastasis.

[0056] S022. Based on the status indicator, obtain the monitoring target's demand index for different auxiliary treatment labels.

[0057] The demand index described in the present invention is used to quantify the degree of demand for specific auxiliary treatment measures of the monitored target, which reflects the importance or necessity of specific auxiliary treatment dimensions (such as nutritional support, psychological counseling, pain management, etc.) for the current monitoring target.

[0058] It can be understood that the size of the demand index determines the recommendation priority of the auxiliary treatment label, that is, the larger the demand index, the higher the recommendation priority, thereby ensuring the personalization and accuracy of the treatment plan.

[0059] In this embodiment, the step S022 of obtaining the monitoring target's demand index for different auxiliary treatment labels based on the state indicator includes the following steps:

[0060] S0221. Obtain the impact parameters of different auxiliary treatment labels on the status indicators respectively.

[0061] In this embodiment, the auxiliary treatment label includes a dietary intervention label and a psychological intervention label.

[0062] It can be understood that, in some other embodiments, the auxiliary treatment label may include other measure dimension labels, or may be other measure dimension labels.

[0063] Based on the status indicator analysis of the monitoring target in step S021, the influencing parameters of any auxiliary treatment label on the status indicator obtained in step S0221 include: a first status indicator influencing parameter, a second status indicator influencing parameter, a third status indicator influencing parameter and a fourth status indicator influencing parameter.

[0064] It can be understood that, in some other embodiments, the influence parameter of any auxiliary treatment label on the state indicator obtained in step S0221 may include other state indicator parameters, or may be other state indicator parameters, which is specifically determined by the state indicator obtained in step S021.

[0065] Furthermore, the influence parameter of any auxiliary treatment label on the state index includes the following acquisition steps:

[0066] S02211. Obtain a sample data set, wherein any sample in the sample data set is an effect score of an auxiliary treatment measure corresponding to an auxiliary treatment label on a set of status indicators.

[0067] Furthermore, any sample satisfies the following characterization model: ,in, represents the effect score of the jth adjuvant treatment label, Indicates the first status indicator of the monitoring target, Indicates the second status indicator of the monitoring target, Indicates the nth status indicator of the monitoring target.

[0068] S02212. Using the sample data set, fit the impact parameters of the auxiliary treatment label on each state indicator in the effect scoring model, so that the difference between the predicted effect score and the actual effect score of all samples by the effect scoring model is minimized.

[0069] Furthermore, the effect scoring model is: ,in, represents the predicted effect score of the jth adjuvant therapy label, represents the first state indicator influencing parameter of the j-th auxiliary treatment label, represents the first state indicator, represents the second state indicator impact parameter of the j-th auxiliary treatment label, represents the second state indicator, represents the nth state indicator influencing parameter of the jth auxiliary treatment label, Represents the nth state indicator.

[0070] When fitting the influencing parameters, the objective function can be solved using the gradient descent method, and the objective function is: , + + ,in, To minimize the objective function, represents the number of samples, g represents the sample number, represents the g-th sample, represents the predicted effect score of the j-th adjuvant treatment label corresponding to the g-th sample, It represents the first state indicator influence parameter of the jth auxiliary treatment label corresponding to the gth sample, represents the first state indicator corresponding to the g-th sample, Indicates the second state indicator influence parameter of the jth auxiliary treatment label corresponding to the gth sample, represents the second state indicator corresponding to the g-th sample, represents the nth state indicator influence parameter of the jth auxiliary treatment label corresponding to the gth sample, Represents the nth state indicator corresponding to the gth sample.

[0071] S0222. Based on the influencing parameters of different auxiliary treatment labels, respectively obtain demand indexes of different auxiliary treatment labels.

[0072] Furthermore, the demand index of any auxiliary treatment label satisfies the following calculation model: , where j represents the number of the adjuvant therapy label, represents the monitoring target's demand index for the jth auxiliary treatment label, i represents the number of the status indicator, Indicates the number of status indicators, represents the i-th state indicator influence parameter of the j-th auxiliary treatment label, Represents the i-th state indicator.

[0073] S023. Based on the monitoring target's demand index for different auxiliary treatment labels, select at least one target auxiliary treatment label from different auxiliary treatment labels.

[0074] In this embodiment, the step S023 of selecting at least one target auxiliary treatment label from different auxiliary treatment labels based on the monitoring target's demand index for different auxiliary treatment labels includes the following steps:

[0075] S0231. Based on the tumor staging results, obtain a demand index threshold.

[0076] The demand index threshold described in the present invention is a standard for measuring the intensity of the demand for different auxiliary treatment measures (such as nutritional support, psychological support, pain management, etc.) of the monitored target.

[0077] In this embodiment, the magnitude of the demand index threshold is related to the cancer staging result of the monitoring target. Further, the demand index threshold can be set according to the demand index distribution of different auxiliary treatment measures at different cancer staging stages.

[0078] Generally speaking, when the monitored target is in the early stage of cancer, the demand index threshold is high, because the monitored target's body function can still cope with the primary treatment, and the need for auxiliary treatment is not so urgent; when the monitored target is in the middle stage of cancer, the demand index threshold is lowered to ensure that the monitored target can obtain sufficient rehabilitation support; when the monitored target is in the late stage of cancer, the demand index threshold is further lowered to ensure that the monitored target can get more rehabilitation support in a timely manner.

[0079] S0232. Based on the demand index threshold, select at least one target auxiliary treatment label from different auxiliary treatment labels according to a selection rule.

[0080] Furthermore, the selection rules include the following: if there is an auxiliary therapy label whose demand index is greater than or equal to the demand index threshold, one or more auxiliary therapy labels whose demand index is greater than or equal to the demand index threshold are set as the target auxiliary therapy label; if there is no auxiliary therapy label whose demand index is greater than or equal to the demand index threshold, the auxiliary therapy label with the largest demand index is set as the target auxiliary therapy label.

[0081] S03. The node setting module sets at least one implementation node according to the implementation frequency of the target auxiliary treatment tag, and the implementation node is a time node for implementing auxiliary treatment measures.

[0082] Understandably, different adjunctive therapy labels have different implementation frequencies. For example, nutritional support may need to be implemented daily, pain management may be adjusted over time based on monitoring goal feedback and symptom development, and psychological support may be implemented weekly or monthly.

[0083] Specifically, step S03 can set an initial implementation node for each target auxiliary treatment tag according to the demand index of the monitoring target; as the condition of the monitoring target changes, the initial implementation node or the implementation node set last time is dynamically adjusted according to the feedback of the monitoring target.

[0084] For example, the tumor stage of a child tumor monitoring target is T2N1M0, and the monitoring target is in the mid-stage of cancer. The demand index assessment shows that the monitoring target has a high demand for nutritional support; based on this, the system generates a target auxiliary treatment label for the monitoring target - the dietary intervention label; the system sets the implementation nodes of the dietary intervention label to fixed times every day: 8:00 (before breakfast), 12:00 (before lunch), and 18:00 (before dinner) for nutritional supplement support, and each nutritional support measure is a nutritional meal supplement or oral nutritional supplement. The guardian of the monitoring target reported that his physical strength has declined rapidly recently. The system further shortened the implementation interval of nutritional support based on the feedback information, and the adjusted implementation nodes will become: 8:00 (before breakfast), 12:00 (before lunch), 15:00 (snack), and 18:00 (before dinner).

[0085] S04. The interaction setting module sets an interaction window based on the interaction object of the target auxiliary treatment label, and the interaction window is used to visualize the implementation node and the auxiliary treatment measures corresponding to the implementation node to the interaction object, and to obtain feedback information of the interaction object based on the auxiliary treatment measures.

[0086] It can be understood that the interactive window is a bridge connecting the monitoring target, the monitoring personnel of the monitoring target, the medical staff and the system. It can not only intuitively display the implementation nodes of auxiliary treatment, but also display the auxiliary treatment measures corresponding to each node. At the same time, it collects user feedback information based on these auxiliary treatment measures, so as to facilitate the system to dynamically adjust and optimize the treatment plan.

[0087] Furthermore, the system displays specific treatment measures (such as nutritional support, psychological support, pain management, etc.) on the interactive window according to the set implementation nodes, and the monitored targets and medical staff can view them in real time; before each implementation node, the system reminds the monitored targets or caregivers through the interactive window to ensure that the treatment measures are executed within the scheduled time, for example, by popping up reminder messages or sending notifications through mobile phones, tablets or computer interfaces; after completing the treatment measures, the monitored targets or caregivers submit feedback through the interactive window, and the feedback content may include the monitored targets' subjective feelings (such as pain relief, improved mental state, etc.) and objective physiological data (such as body temperature, blood pressure, heart rate, etc.).

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents.

Claims

1. A pediatric tumor management system based on diet and psychological intervention, characterized in that: include: A data acquisition module, wherein the data acquisition module is used to obtain the tumor staging result of the monitored target, wherein the tumor staging result is a quantitative evaluation result of the tumor development status; A label setting module, the label setting module is used to set at least one target auxiliary treatment label based on the tumor staging result, the target auxiliary treatment label is a measure dimension label for assisting in monitoring the treatment of the target tumor; A node setting module, the node setting module is used to set at least one implementation node according to the implementation frequency of the target auxiliary treatment tag, and the implementation node is a time node for implementing the auxiliary treatment measure; An interaction setting module, the interaction setting module is used to set an interaction window based on the interaction object of the target auxiliary treatment label, the interaction window is used to visualize the implementation node and the auxiliary treatment measures corresponding to the implementation node to the interaction object, and is used to obtain feedback information of the interaction object based on the auxiliary treatment measures; The step of setting at least one target auxiliary treatment tag based on the tumor staging result comprises the following steps: using the tumor staging result to obtain a state indicator of a monitoring target; Based on the status indicators, obtaining a demand index of the monitoring target for different auxiliary treatment labels; Based on the monitoring target's demand index for different auxiliary treatment labels, selecting at least one target auxiliary treatment label from different auxiliary treatment labels; The step of obtaining the demand index of the monitoring target for different auxiliary treatment labels based on the state index comprises the following steps: respectively obtaining the influence parameters of different auxiliary treatment labels on the state index; and respectively obtaining the demand index of different auxiliary treatment labels based on the influence parameters of different auxiliary treatment labels. The demand index of any auxiliary treatment label satisfies the following calculation model: , where j represents the number of the adjuvant therapy label, represents the monitoring target's demand index for the jth auxiliary treatment label, i represents the number of the status indicator, Indicates the number of status indicators, represents the i-th state indicator influence parameter of the j-th auxiliary treatment label, represents the i-th state indicator; In the step of obtaining the influence parameters of different auxiliary treatment labels on the state indicators, the influence parameters of any auxiliary treatment label on the state indicators include the following obtaining steps: obtaining a sample data set, wherein any sample in the sample data set is an effect score of an auxiliary treatment measure corresponding to an auxiliary treatment label on a group of state indicators; using the sample data set, fitting the influence parameters of the auxiliary treatment label on each state indicator in the effect scoring model, so that the difference between the predicted effect score and the actual effect score of all samples by the effect scoring model is minimized, and the effect scoring model is: ,in, represents the predicted effect score of the jth adjuvant therapy label, represents the first state indicator influencing parameter of the j-th auxiliary treatment label, represents the first state indicator, represents the second state indicator impact parameter of the j-th auxiliary treatment label, represents the second state indicator, represents the nth state indicator influencing parameter of the jth auxiliary treatment label, Represents the nth state indicator.

2. The pediatric tumor management system based on diet and psychological intervention according to claim 1, characterized in that: The data acquisition module is connected to an electronic medical record system that stores the medical records of the monitored target. The step of obtaining the tumor staging result of the monitored target includes the following steps: obtaining the identity information of the monitored target, and extracting the tumor staging result of the monitored target from the electronic medical record system based on the identity information.

3. The pediatric tumor management system based on diet and psychological intervention according to claim 1, characterized in that: The method of using the tumor staging result to obtain the status indicator of the monitoring target includes the following steps: Obtaining a first status indicator based on the tumor type in the tumor staging result; Obtaining a second status indicator based on the tumor size in the tumor staging result; Based on the lymph node invasion status in the tumor staging result, a third status indicator is obtained; Based on the tumor metastasis situation in the tumor staging result, a fourth status indicator is obtained.

4. The pediatric tumor management system based on diet and psychological intervention according to claim 3, characterized in that: The auxiliary treatment label includes a dietary intervention label and a psychological intervention label.

5. The pediatric tumor management system based on diet and psychological intervention according to claim 4, characterized in that: The objective function of the effect scoring model fitting is: , + + ,in, To minimize the objective function, represents the number of samples, g represents the sample number, represents the g-th sample, represents the predicted effect score of the j-th adjuvant treatment label corresponding to the g-th sample, It represents the first state indicator influence parameter of the jth auxiliary treatment label corresponding to the gth sample, represents the first state indicator corresponding to the g-th sample, Indicates the second state indicator influence parameter of the jth auxiliary treatment label corresponding to the gth sample, represents the second state indicator corresponding to the g-th sample, represents the nth state indicator influence parameter of the jth auxiliary treatment label corresponding to the gth sample, Represents the nth state indicator corresponding to the gth sample.

6. The pediatric tumor management system based on diet and psychological intervention according to claim 1, characterized in that: The step of selecting at least one target auxiliary treatment label from different auxiliary treatment labels based on the monitoring target's demand index for different auxiliary treatment labels comprises the following steps: Based on the tumor staging result, a demand index threshold is obtained; Based on the demand index threshold, at least one target auxiliary therapy tag is selected from different auxiliary therapy tags according to a selection rule, and the selection rule includes the following: If there is an auxiliary treatment tag whose demand index is greater than or equal to the demand index threshold, one or more auxiliary treatment tags whose demand index is greater than or equal to the demand index threshold are all set as target auxiliary treatment tags; If there is no auxiliary treatment tag with a demand index greater than or equal to the demand index threshold, the auxiliary treatment tag with the largest demand index is set as the target auxiliary treatment tag.

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