Breast cancer patient whole-course intelligent individual case management system and method

Abstract

The invention discloses a whole-course intelligent individual case management system and method for a breast cancer patient, relates to the technical field of intelligent individual case management, and aims to solve the problems that the treatment process of the breast cancer patient is inconvenient and the treatment effect is poor. Feedback information is evaluated through a rehabilitation evaluation algorithm built in the individual case management port, personalized rehabilitation suggestions are generated, the treatment effect and the patient satisfaction degree can be improved, a treatment scheme is fed back in real time and dynamically adjusted, a doctor can more accurately control the treatment process, and therefore the treatment efficiency is improved, and the treatment cost is reduced. A real-time feedback mechanism enables medical staff to timely discover and process abnormal reactions of patients, medical risks are reduced, complex health data can be effectively processed by using an FFCA technology to construct an illness state assessment model, the accuracy and efficiency of data analysis are improved, similar patient features can be classified through clustering analysis, and the accuracy and efficiency of medical analysis are improved. And potential illness state modes and trends can be identified.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent case management, and specifically to an intelligent case management system and method for breast cancer patients throughout the whole process. Background Art

[0002] The intelligent case management of breast cancer patients refers to providing personalized, systematic, and continuous medical and health management services for breast cancer patients by using modern information technology, especially artificial intelligence technology.

[0003] Chinese Patent with publication number CN215600099U discloses a patient case management and tracking system, which mainly combines integrated sensor devices with mobile technology, can record patient information and intelligently track the treatment progress of patients, remind medical staff to follow up in time and track the rehabilitation status of patients, facilitate medical staff, patients and their families to monitor the patient's condition at any time, facilitate the hospital to conduct effective follow-up treatment on patients, ensure that the patient's condition can be treated in time, and at the same time, it is also convenient for medical staff to extract the patient's condition tracking progress at any time and analyze the condition. Although the above patent solves the problem of patient case management, there are still the following problems in actual operation: 1. After obtaining the patient's health data, no more meticulous disease diagnosis and analysis are carried out, resulting in the inability to formulate a more complete plan according to the condition.

[0004] 2. No targeted treatment plan is formulated according to the actual condition of the patient, and no more perfect treatment reminder is carried out during the implementation of the treatment plan for the patient, resulting in poor treatment effect of the patient.

[0005] 3. No targeted expert consultation and post-treatment monitoring are carried out on the feedback and rehabilitation status during the patient's treatment process, resulting in poor treatment effect of the patient. Summary of the Invention

[0006] The purpose of the present invention is to provide an intelligent case management system and method for breast cancer patients throughout the whole process. By using the rehabilitation evaluation algorithm built in the case management port to evaluate the feedback information and generate personalized rehabilitation suggestions, it helps to improve the treatment effect and patient satisfaction. The real-time feedback and dynamic adjustment of the treatment plan help doctors control the treatment process more precisely, thereby improving the treatment efficiency. The real-time feedback mechanism enables medical staff to detect and handle the abnormal reactions of patients in time, reducing the medical risk. Using the FFCA technology to construct a disease evaluation model can effectively process complex health data, improving the accuracy and efficiency of data analysis. Through cluster analysis, similar patient characteristics can be classified to help identify potential disease patterns and trends, and the problems in the prior art can be solved.

[0007] To achieve the above object, the present invention provides the following technical solutions: The intelligent case management system for breast cancer patients includes: Patient information collection unit, used for: The patient registers the case management port on the mobile terminal, enters the health data after registration, and pre-processes the data after the health data is entered. After the data is pre-processed, the target health data is obtained; Data Brain Chip Diagnostic Unit, used for: Use FFCA technology to build a disease assessment model for target health data, combine the constructed disease assessment model with the brain-like chip and perform intelligent analysis and diagnosis. After the intelligent analysis and diagnosis is completed, the patient's diagnostic data is obtained; Intervention Planning Unit to: Formulate intervention plans based on patient diagnostic data, and convert the formulated intervention plans into visual data. After the visual data conversion is completed, the patient treatment plan is obtained; Intervention Program Coordination Unit to: The patient can view the patient's treatment plan in the case management port, and perform treatment according to the content of the patient's treatment plan. In addition, the case management port can assist in medication according to the treatment content of the patient's treatment plan; The data brain chip diagnostic unit is also used for: Confirming feature data in the target health data, and performing context-aware analysis on the confirmed feature data, wherein the context-aware analysis includes time context and environmental context; The feature data after context-aware analysis is used to build a disease assessment model using FFCA technology; The disease assessment model is constructed by first using FFCA technology to perform cluster analysis on the feature data after context-aware analysis; After cluster analysis, a recurrent neural network was used to construct a disease assessment model, and the constructed disease assessment model was optimized and verified.

[0008] Preferably, the data brain chip diagnostic unit optimizes and verifies the constructed disease assessment model, including: Extracting verification data corresponding to multiple different disease characteristics from the verification data set, and obtaining verification training data and verification result data from each verification data; Based on the impact of different disease characteristics on breast cancer patients, the corresponding validation weights of validation training data are set; The disease assessment model is verified based on the verification training data and the verification result data to obtain the deviation and variance of the model under each disease characteristic; Based on the bias and variance of the model under each disease condition feature, the model evaluation value K of the disease condition evaluation model is calculated according to the following formula; where n represents the number of disease condition features, represents the verification weight of the i-th disease condition feature, represents the bias value of the i-th disease condition feature, represents the variance value of the i-th disease condition feature, represents the standard deviation value, represents the standard variance value, represents a constant; Judge whether the model evaluation value is greater than a preset evaluation value; If so, it is determined that the disease condition evaluation model does not need to be optimized; Otherwise, it is determined that the disease condition evaluation model needs to be optimized; Based on the model evaluation value, the optimization weight F for the disease condition evaluation model is determined according to the following formula; where, represents the average standard weight, represents the preset evaluation value; Obtain the optimization scheme corresponding to the optimization weight from the preset optimization scheme set and optimize the disease condition evaluation model.

[0009] Preferably, the data brain-like chip diagnosis unit is further configured to: Adapt the optimized and verified disease condition evaluation model to the interface of the brain-like chip; After the adaptation process is completed, deploy the optimized and verified disease condition evaluation model to the brain-like chip; The brain-like chip uses pattern recognition and neural network algorithms to perform real-time diagnosis on the received disease condition evaluation model; The diagnosis results include the severity, type, development stage and involved complications of the patient's disease condition; After the diagnosis is completed, the patient's diagnosis data is obtained.

[0010] Preferably, the patient information collection unit is further configured to: The patient uses a mobile terminal to scan the code and register for the case management port. After the registration is completed, the patient logs in to the case management port and enters personal health data; where the personal health data includes the patient's basic information, medical history information, physiological indicators, biochemical indicators, historical treatment information, living habits, psychological state, current physical symptoms and drug use conditions; Preprocess the entered health data, including data cleaning, data standardization, data conversion, feature extraction and data integration; After data preprocessing is completed, the target health data is obtained.

[0011] Preferably, the data brain chip diagnostic unit uses a recurrent neural network to construct a disease assessment model after cluster analysis, including: An initial model building unit is used to obtain feature data after cluster analysis, and perform feature selection and feature conversion on the feature data based on multiple disease assessment requirements to obtain multiple target feature sets, and train the multiple target feature sets based on a recurrent neural network to obtain multiple initial assessment models; A model integration unit is used to adjust and verify the hyperparameters of the multiple initial evaluation models, obtain the multiple reference evaluation models corresponding to the optimal hyperparameters, obtain the prediction results of the multiple reference evaluation models, and train the prediction results based on a recurrent neural network to obtain a comprehensive evaluation model; A model comparison unit, used to obtain model structure differences between the comprehensive evaluation model and multiple reference evaluation models, and determine whether the model structure differences are all within a preset difference range; If so, the comprehensive evaluation model is used as the target evaluation model; Otherwise, the model structure of the comprehensive evaluation model is modified based on the model structure difference, and the target evaluation model is obtained according to the modification result; The model simplification unit is used to simplify the target assessment model based on the model generalization capability requirements to obtain the final disease assessment model. Preferably, the intervention program formulation unit is further used for: Before formulating an intervention plan, the patient’s diagnostic data should be analyzed in depth; After in-depth analysis, the patient's symptom characteristics, risk assessment information and individual characteristics in the patient's diagnostic data were obtained; Construct a treatment plan framework based on the patient's diagnostic data, which includes drug therapy, surgical treatment, radiotherapy, chemotherapy and lifestyle intervention; Refine the treatment plan based on the treatment plan framework and in-depth analysis of patient diagnostic data, including specific steps, timetable and expected goals of treatment; Then, the drug type, dosage, administration time and administration method are confirmed based on the patient's drug use and treatment response; Annotate treatment side effects based on detailed treatment regimen and patient medication selection; The final treatment plan is converted into a visual form of charts and timelines for presentation, and the patient's treatment plan, treatment time, medication status, and side effect notes are obtained after presentation; Label the treatment plan in visual form as the patient's treatment plan.

[0012] Preferably, the intervention plan coordination unit is further used for: After logging into the case management portal on a mobile terminal, the patient can view the patient's treatment plan; The patient receives treatment according to the treatment method and treatment time in the patient's treatment plan, and the patient will feedback the reaction and side effects to the case management port during the treatment process; At the same time, the case management port provides medication assistance reminders based on the type, dosage, administration time and administration method of the drug in the patient's treatment plan; The reminder method is to send the drug type, dosage, administration time and administration method to the patient's mobile terminal for reminder.

[0013] Preferably, it also includes a rehabilitation tracking and supervision unit, which is used to: When patients receive treatment according to the treatment plan, treatment feedback is recorded in real time. The case management port conducts rehabilitation assessment based on the feedback record, generates rehabilitation suggestions based on the rehabilitation assessment results, and displays the generated rehabilitation suggestions visually. Among them, during the treatment process, patients log in to the case management port through mobile terminals and input feedback information in real time; Feedback includes treatment implementation, symptoms or side effects, psychological status and impact on daily life, and unexpected events; The case management port receives the feedback information, and a rehabilitation assessment algorithm is built into the case management port, and the rehabilitation assessment algorithm performs rehabilitation assessment on the feedback information; The rehabilitation assessment process includes symptom analysis, side effect assessment, and treatment compliance assessment; Based on the results of the rehabilitation assessment, the case management portal generates personalized rehabilitation recommendations; Recovery recommendations include treatment modification, side effect management, lifestyle adjustments, and psychological counseling; The rehabilitation suggestions are converted into visual form and then transmitted to the mobile terminal for display after the visual conversion.

[0014] Preferably, it also includes a remote monitoring consultation unit, which is used for: The case management port transmits the patient's feedback records and rehabilitation suggestions to the remote consultation platform for expert consultation, and performs monitoring and treatment based on the consultation results; Among them, the patient's feedback records and rehabilitation suggestions are summarized and the summarized data is encrypted; The case management portal logs into the remote consultation platform via a secure network connection; The encrypted summary data is uploaded to the remote consultation platform, wherein the case management port confirms the completion of data transmission and receives confirmation information from the remote consultation platform; After the remote consultation platform receives the data, the expert logs in to the remote consultation platform to view the patient's feedback records and rehabilitation suggestions; Professional analysis will be conducted based on the feedback records and rehabilitation suggestions, and consultation opinions will be obtained after professional analysis; The remote consultation platform transmits the consultation opinions to the case management port, which organizes the consultation opinions into documents, and the case management port monitors the patients according to the documents; Custody management includes adjustment of treatment regimen and enhanced monitoring measures.

[0015] Intelligent case management method for breast cancer patients throughout the process, including: S1: The patient first registers the case management port on the mobile terminal and enters personal health data after registration; S2: The case management port uses the patient’s personal health data to assess and diagnose the condition; S3: The case management port formulates a treatment plan for the patient based on the condition assessment and diagnosis results; S4: The patient opens the case management port on the mobile terminal to view and execute the treatment plan; S5: The patient records the feedback information during the treatment process in a timely manner, and the case management port generates rehabilitation suggestions based on the feedback information; S6: The case management port transmits the rehabilitation suggestions and feedback records to the remote consultation platform for expert consultation. The remote consultation platform transmits the consultation records to the case management port, and the case management port generates monitoring processing results for the consultation records.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. The intelligent case management system and method for breast cancer patients provided by the present invention can effectively process complex health data and improve the accuracy and efficiency of data analysis by using FFCA technology to construct a disease assessment model. Similar patient characteristics can be classified through cluster analysis to help identify potential disease patterns and trends. The recurrent neural network is used to construct a disease assessment model, which can process time series data, capture the dynamic characteristics of the patient's health status changing over time, and improve the accuracy of prediction.

[0017] 2. The whole-process intelligent case management system and method for breast cancer patients provided by the present invention enable medical staff to more effectively evaluate the treatment effect through data analysis, timely adjust the treatment plan, thereby improving the utilization efficiency of medical resources. The real-time feedback mechanism enables medical staff to timely detect and handle the abnormal reactions of patients, reducing medical risks. Confirming the types, dosages, administration times, and administration methods of drugs according to the drug use conditions and treatment reactions of patients reflects the dynamics and flexibility of the treatment plan. Timely adjusting the treatment plan can cope with the changes in the patient's condition and ensure the treatment effect.

[0018] 3. The whole-process intelligent case management system and method for breast cancer patients provided by the present invention. The case management port evaluates the feedback information through the built-in rehabilitation assessment algorithm and generates personalized rehabilitation suggestions, which helps to improve the treatment effect and patient satisfaction. The real-time feedback and dynamic adjustment of the treatment plan help doctors more precisely control the treatment process, thereby improving the treatment efficiency. Medical staff can real-time track the patient's rehabilitation progress, timely adjust the treatment plan and strengthen monitoring measures, improving the continuity and pertinence of medical services. Remote consultation and case management reduce the number of times patients travel to the hospital, saving time and energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the whole-process intelligent case management unit for breast cancer patients of the present invention; Figure 2 It is a schematic diagram of the whole-process intelligent case management process for breast cancer patients of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0021] To solve the problem in the prior art that after obtaining the health data of patients, no more careful diagnosis and analysis of the condition are carried out, resulting in the inability to formulate a more complete plan according to the condition of the disease, please refer to Figure 1 and Figure 2 , the following technical solutions are provided in this embodiment: The whole-process intelligent case management system for breast cancer patients includes: A patient information collection unit, which is used for: The patient registers at the case management port on the mobile terminal. After the registration is completed, health data is entered. After the health data entry is completed, data preprocessing is performed, and target health data is obtained after the data preprocessing; Data Brain Chip Diagnostic Unit, used for: Use FFCA technology to build a disease assessment model for target health data, combine the constructed disease assessment model with the brain-like chip and perform intelligent analysis and diagnosis. After the intelligent analysis and diagnosis is completed, the patient's diagnostic data is obtained; Intervention Planning Unit to: Formulate intervention plans based on patient diagnostic data, and convert the formulated intervention plans into visual data. After the visual data conversion is completed, the patient treatment plan is obtained; Intervention Program Coordination Unit to: The patient can view the patient's treatment plan in the case management port, and perform treatment according to the content of the patient's treatment plan. In addition, the case management port can assist in medication according to the treatment content of the patient's treatment plan; Rehabilitation follow-up supervision unit is used to: When patients receive treatment according to the treatment plan, treatment feedback is recorded in real time. The case management port conducts rehabilitation assessment based on the feedback record, generates rehabilitation suggestions based on the rehabilitation assessment results, and displays the generated rehabilitation suggestions visually. Remote monitoring consultation unit for: The case management port transmits the patient's feedback records and rehabilitation suggestions to the remote consultation platform for expert consultation, and performs monitoring and treatment based on the consultation results.

[0022] Specifically, through the patient information collection unit, patients can update their health data at any time, medical institutions can continuously track the health status of patients and promptly identify potential health problems. The data brain chip diagnostic unit provides doctors with scientific decision-making support to help them develop more reasonable treatment plans and improve the quality of medical services. The visual treatment plan of the intervention plan formulation unit is also convenient for recording and tracking the patient's treatment progress and medication status. The convenience of the mobile terminal of the intervention plan coordination unit allows patients to view treatment plans and medication reminders anytime and anywhere, thereby improving the flexibility and convenience of treatment. The personalized rehabilitation suggestions and optimized treatment plans of the rehabilitation tracking and supervision unit are more likely to improve the treatment effect and promote the patient's rehabilitation. Through the remote monitoring consultation unit, medical staff can track the patient's rehabilitation progress in real time, adjust the treatment plan and strengthen monitoring measures in a timely manner, thereby improving the continuity and pertinence of medical services.

[0023] The patient information collection unit is also used for: The patient uses a mobile terminal to scan the code on the case management port to register. After registration, the patient logs in to the case management port and enters personal health data; Among them, personal health data includes the patient's basic information, medical history information, physiological indicators, biochemical indicators, historical treatment information, living habits, psychological state, current physical symptoms and medication use; Preprocess the entered health data, including data cleaning, data standardization, data conversion, feature extraction and data integration; After data preprocessing is completed, the target health data is obtained.

[0024] Specifically, patients can scan the code to register and log in to the case management port anytime and anywhere through mobile terminals to enter their personal health data. This flexibility greatly improves the convenience of data entry, allowing patients to operate according to their own schedule and actual situation. Registering and entering data through mobile terminals avoids the cumbersome process of traditional paper filling, reduces patients' waiting time and the administrative burden of medical institutions. The data preprocessing process includes data cleaning, data standardization, data conversion and other steps, which can remove duplicate, redundant and erroneous data, fill in missing values, and ensure the accuracy and completeness of data. Data preprocessing can also unify and convert data from different sources and formats, making data easier to analyze and use. Patients can update their health data at any time, and medical institutions can continue to track patients' health status and detect potential health problems in a timely manner.

[0025] The data brain chip diagnostic unit is also used for: Confirming feature data in the target health data, and performing context-aware analysis on the confirmed feature data, wherein the context-aware analysis includes time context and environmental context; The feature data after context-aware analysis is used to build a disease assessment model using FFCA technology; The disease assessment model is constructed by first using FFCA technology to perform cluster analysis on the feature data after context-aware analysis; After cluster analysis, a recurrent neural network is used to construct a disease assessment model, and the constructed disease assessment model is optimized and verified; Adapt the optimized and verified disease assessment model to the interface of the brain-like chip; After the adaptation process is completed, the optimized and verified disease assessment model will be deployed on the brain-like chip; The brain-like chip uses pattern recognition and neural network algorithms to perform real-time diagnosis on the received disease assessment model; The diagnosis includes the severity, type, stage of development and complications involved in the patient's condition; After the diagnosis is completed, the patient's diagnostic data is obtained.

[0026] After cluster analysis in the data brain chip diagnosis unit, a recurrent neural network is used to construct a disease assessment model, including: An initial model building unit is used to obtain feature data after cluster analysis, and perform feature selection and feature conversion on the feature data based on multiple disease assessment requirements to obtain multiple target feature sets, and train the multiple target feature sets based on a recurrent neural network to obtain multiple initial assessment models; A model integration unit is used to adjust and verify the hyperparameters of the multiple initial evaluation models, obtain the multiple reference evaluation models corresponding to the optimal hyperparameters, obtain the prediction results of the multiple reference evaluation models, and train the prediction results based on a recurrent neural network to obtain a comprehensive evaluation model; A model comparison unit, used to obtain model structure differences between the comprehensive evaluation model and multiple reference evaluation models, and determine whether the model structure differences are all within a preset difference range; If so, the comprehensive evaluation model is used as the target evaluation model; Otherwise, the model structure of the comprehensive evaluation model is modified based on the model structure difference, and the target evaluation model is obtained according to the modification result; The model simplification unit is used to simplify the target assessment model based on the model generalization capability requirements to obtain a final disease assessment model.

[0027] The beneficial effects of the above design scheme are: by performing feature selection and feature conversion on the feature data based on multiple disease assessment requirements, multiple target feature sets are obtained to realize the training of multiple models, and the accuracy of the model is guaranteed by verifying the hyperparameters of the model. Then, the model is integrated to obtain a comprehensive evaluation model, and the comprehensive evaluation model is corrected based on multiple reference evaluation models to obtain the recognition and evaluation ability of the target evaluation model for each target feature. Finally, based on the model generalization ability requirements, the target evaluation model is simplified to obtain the final disease assessment model, which ensures the generalization ability of the model and provides an accurate model basis for diagnosing the patient's condition.

[0028] The data brain chip diagnostic unit optimizes and verifies the constructed disease assessment model, including: Extracting verification data corresponding to multiple different disease characteristics from the verification data set, and obtaining verification training data and verification result data from each verification data; Based on the impact of different disease characteristics on breast cancer patients, the corresponding validation weights of validation training data are set; The disease assessment model is verified based on the verification training data and the verification result data to obtain the deviation and variance of the model under each disease characteristic; Based on the deviation and variance of the model under each disease characteristic, the model evaluation value K of the disease assessment model is calculated according to the following formula; Where n represents the number of disease characteristics, represents the verification weight of the i-th disease feature, represents the deviation value of the i-th disease feature, represents the variance value of the i-th disease characteristic, represents the standard deviation value, represents the standard deviation value, represents a constant; Determining whether the model evaluation value is greater than a preset evaluation value; If so, determining that the condition assessment model does not need to be optimized; Otherwise, determining that the condition assessment model needs to be optimized; Based on the model evaluation value, the optimization weight F of the condition assessment model is determined according to the following formula; in, represents the average standard weight, Indicates the preset evaluation value; The optimization scheme corresponding to the optimization weight is obtained from a preset optimization scheme set to optimize the condition assessment model.

[0029] In this embodiment, the variance value, the standard deviation value, and the constant are preset according to actual conditions.

[0030] In this embodiment, different disease characteristics, such as the degree of canceration and the area of ​​canceration of breast cancer patients, are classified. The greater the impact of the disease characteristics on breast cancer patients, the greater the corresponding expedition weight.

[0031] In this embodiment, the validation result data is used to compare with the predicted values ​​to determine the bias and variance.

[0032] In this embodiment, the preset optimization solution set predefines the solution content and the corresponding relationship between the solution and the optimization weight according to the specific situation.

[0033] The beneficial effects of the above design scheme are: by setting the verification weight of the corresponding verification training data based on the degree of influence of different disease characteristics on breast cancer patients, the disease assessment model is verified based on the verification training data and the verification result data, and the deviation and variance of the model under each disease characteristic are obtained to calculate the model evaluation value, and the determined model evaluation value is made to better meet the actual needs through classification verification. Based on the model evaluation value, the verification weight is considered to determine the optimization of the model, so as to ensure that the optimized model better meets the actual needs and provide an accurate model basis for the diagnosis of the patient's disease.

[0034] Specifically, by performing context-aware analysis of patient characteristic data (including time and environmental context), we can better understand the patient's specific situation and provide personalized disease assessment and treatment plans. Using FFCA technology to build a disease assessment model can effectively process complex health data and improve the accuracy and efficiency of data analysis. Cluster analysis can classify similar patient characteristics to help identify potential disease patterns and trends. Using recurrent neural networks to build disease assessment models can process time series data, capture the dynamic characteristics of patients' health status over time, and improve the accuracy of predictions. The optimized disease assessment model is deployed on brain-like chips, and pattern recognition and neural network algorithms are used for real-time diagnosis, which can quickly respond to changes in patients' health and provide accurate predictions. Provide timely medical intervention. The diagnostic results include not only the severity, type and development stage of the patient's condition, but also the identification of complications. It provides a comprehensive health assessment to help doctors develop more effective treatment plans. By optimizing and verifying the constructed disease assessment model, the reliability and effectiveness of the model are ensured, and the risks of misdiagnosis and missed diagnosis are reduced. Through data analysis and model construction, scientific decision-making support is provided to doctors to help them develop more reasonable treatment plans and improve the quality of medical services. Patients can understand their own disease assessment process and results, enhance their trust and sense of participation in the treatment plan, and promote patients' self-management and health awareness. The interface adaptation processing between the model and the brain-like chip enables the system to be flexibly adjusted according to the needs of different patients and adapt to different clinical scenarios.

[0035] In order to solve the problem that the existing technology does not formulate targeted treatment plans according to the actual condition of the patient, and does not provide more complete treatment reminders to the patient during the implementation of the treatment plan, resulting in poor treatment effects for the patient, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions: The Intervention Planning Unit is also used to: Before formulating an intervention plan, the patient’s diagnostic data should be analyzed in depth; After in-depth analysis, the patient's symptom characteristics, risk assessment information and individual characteristics in the patient's diagnostic data were obtained; Construct a treatment plan framework based on the patient's diagnostic data, which includes drug therapy, surgical treatment, radiotherapy, chemotherapy and lifestyle intervention; Refine the treatment plan based on the treatment plan framework and in-depth analysis of patient diagnostic data, including specific steps, timetable and expected goals of treatment; Then, the drug type, dosage, administration time and administration method are confirmed based on the patient's drug use and treatment response; Annotate treatment side effects based on detailed treatment regimen and patient medication selection; The final treatment plan is converted into a visual form of charts and timelines for presentation, and the patient's treatment plan, treatment time, medication status, and side effect notes are obtained after presentation; Label the treatment plan in visual form as the patient's treatment plan.

[0036] Specifically, it emphasizes the in-depth analysis of patient diagnostic data, which is the basis for formulating effective treatment plans. Data-driven can ensure that the treatment plan is more scientific and accurate, avoiding blindness and arbitrariness. After in-depth analysis, the plan takes into account the patient's symptom characteristics, risk assessment information and individual characteristics, which helps to formulate a treatment plan that is more in line with the patient's actual situation. Personalized treatment can improve the treatment effect, reduce unnecessary medical interventions, and improve patient satisfaction and comfort. The treatment plan framework includes a variety of means such as drug therapy, surgical treatment, radiotherapy, chemotherapy and life intervention, which reflects the idea of ​​comprehensive treatment. According to the specific situation of the patient, the most appropriate treatment combination can be selected to achieve the best treatment effect, which is refined to specific steps, timetables and expected goals, making the treatment process clearer and controllable. Both patients and medical staff can clearly understand the progress and expected effects of treatment, which helps to enhance confidence and cooperation in treatment. The type of drug, dosage, administration time and administration method are confirmed according to the patient's drug use and treatment response, which reflects the dynamic and flexibility of the treatment plan. Timely adjustment of treatment plans can respond to changes in the patient's condition and ensure the effectiveness of treatment. Annotations of treatment side effects help patients and medical staff understand possible treatment risks in advance and take corresponding preventive measures or countermeasures. This can improve patient safety, reduce discomfort and complications during treatment, and present treatment plans in the form of charts and timelines, making them more intuitive and easy to understand. This helps patients and medical staff better communicate and understand treatment plans, improve treatment compliance and cooperation, and visual treatment plans are also convenient for recording and tracking patients' treatment progress and medication.

[0037] The Intervention Programme Coordination Unit also serves to: After logging into the case management portal on a mobile terminal, the patient can view the patient's treatment plan; The patient receives treatment according to the treatment method and treatment time in the patient's treatment plan, and the patient will feedback the reaction and side effects to the case management port during the treatment process; At the same time, the case management port provides medication assistance reminders based on the type, dosage, administration time and administration method of the drug in the patient's treatment plan; The reminder method is to send the drug type, dosage, administration time and administration method to the patient's mobile terminal for reminder.

[0038] Specifically, patients can conveniently view their treatment plans through mobile terminals, so as to have a clearer understanding of the treatment steps and expected results. Real-time feedback on reactions and side effects during treatment can help enhance patients' sense of participation and responsibility, and at the same time improve compliance with treatment. Through the case management port, patients can accurately understand the treatment time and treatment methods, reducing treatment delays or errors caused by forgetfulness or misunderstanding. The medication assistance reminder function ensures that patients take medication on time, in the right amount, and in the right way, avoiding missed or overdosing, and improving treatment effects. The case management port can automatically record patients' treatment progress and feedback, reducing the workload of medical staff for manual recording. Through data analysis, medical staff can more effectively evaluate the treatment effect and adjust the treatment plan in time, thereby improving the utilization efficiency of medical resources. The real-time feedback mechanism enables medical staff to promptly discover and deal with patients' abnormal reactions and reduce medical risks. The medication reminder function helps reduce medical accidents caused by improper medication and improve overall medical safety. Patients can feedback problems and concerns during treatment to medical staff through the case management port, enhancing communication and trust between doctors and patients. Medical staff can also provide personalized guidance and suggestions to patients through the portal to improve treatment effects and patient satisfaction. The convenience of mobile terminals allows patients to view treatment plans and medication reminders anytime and anywhere, improving the flexibility and convenience of treatment. Personalized reminder and feedback mechanisms help improve patients' overall satisfaction and experience.

[0039] In order to solve the problem that the existing technology does not provide targeted expert consultation and post-monitoring for the patient's feedback during the treatment process and the recovery status, resulting in poor treatment effects for the patient, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions: The rehabilitation follow-up supervision unit is also used to: During the treatment process, patients log in to the case management portal through mobile terminals and input feedback information in real time; The feedback information includes the treatment execution status, symptoms or side effects that occur, psychological state, impact on daily life, and unexpected events; The case management port receives the feedback information. The case management port has a built-in rehabilitation assessment algorithm, and the rehabilitation assessment algorithm conducts a rehabilitation assessment on the feedback information; The rehabilitation assessment process includes symptom analysis, side effect assessment, and treatment compliance assessment; Based on the results of the rehabilitation assessment, the case management port generates personalized rehabilitation suggestions; The rehabilitation suggestions include treatment plan adjustment, side effect management, lifestyle adjustment, and psychological counseling; The rehabilitation suggestions are visually transformed and then transmitted to the mobile terminal for display.

[0040] Specifically, patients can input feedback information in real time through the mobile terminal, making the treatment process more dynamic and flexible. Real-time feedback helps doctors or the treatment team promptly understand the patient's condition, enabling them to respond quickly. The feedback information covers the treatment execution status, symptoms or side effects, psychological state, impact on daily life, and unexpected events, providing a comprehensive view of the patient's condition. This comprehensive data collection helps more accurately assess the patient's rehabilitation progress and potential problems. The case management port evaluates the feedback information through the built-in rehabilitation assessment algorithm and generates personalized rehabilitation suggestions. These personalized suggestions better meet the specific needs of the patient, helping to improve the treatment effect and patient satisfaction. After the rehabilitation suggestions are visually transformed, they can be displayed on the mobile terminal, enabling the patient to intuitively understand their rehabilitation plan and suggestions. This convenience improves the patient's participation and understanding of the treatment plan. Real-time feedback and dynamic adjustment of the treatment plan help doctors more precisely control the treatment process, thereby improving treatment efficiency. Personalized rehabilitation suggestions and optimized treatment plans are more likely to improve the treatment effect and promote the patient's recovery. Through the interaction between the mobile terminal and the case management port, patients can feel more attention and personalized care. This interaction helps enhance communication and trust between doctors and patients, improving the patient's treatment compliance and satisfaction.

[0041] The remote monitoring and consultation unit is also used for: Summarize the patient's feedback records and rehabilitation suggestions, and encrypt the summarized data; The case management port logs in to the remote consultation platform through a secure network connection; Upload the encrypted summarized data to the remote consultation platform. Among them, the case management port confirms the completion of data transmission and receives the confirmation information from the remote consultation platform; After the remote consultation platform receives the data, experts log in to the remote consultation platform to view the patient's feedback records and rehabilitation suggestions; And conduct professional analysis based on the feedback records and rehabilitation suggestions, and obtain consultation opinions after professional analysis; The remote consultation platform transmits the consultation opinions to the case management port. The case management port organizes the consultation opinions into a document, and the case management port monitors and processes the patient according to the document; The monitoring and processing include adjusting the treatment plan and strengthening the monitoring measures.

[0042] Specifically, after the feedback records and rehabilitation suggestions of the patient are aggregated, they will be encrypted. This ensures the security of the data during transmission and storage, preventing the leakage of sensitive information. The case management port logs in to the remote consultation platform through a secure network connection, further enhancing the security of data transmission. The remote consultation platform enables experts to obtain the patient's feedback records and rehabilitation suggestions across geographical limitations in a timely manner, so as to conduct professional analysis and give consultation opinions. The data transmission confirmation mechanism ensures the integrity and reliability of the data, improving the accuracy and efficiency of the consultation. The case management port can easily organize and analyze the consultation opinions to form a document, providing a personalized monitoring and treatment plan for the patient. Through the case management port, medical staff can track the patient's rehabilitation progress in real time, adjust the treatment plan and strengthen the monitoring measures in a timely manner, improving the continuity and pertinence of medical services. Remote consultation and case management reduce the number of times the patient travels to the hospital, saving time and energy and improving the patient's medical experience. Professional consultation opinions and personalized monitoring and treatment plans help the patient better understand and implement the rehabilitation plan, promoting the rehabilitation process. The remote consultation platform enables more effective utilization of medical resources, reducing waste and duplicate investment of medical resources. Through data aggregation and analysis, medical institutions can better understand the rehabilitation needs and problems of patients, so as to optimize the allocation and use of medical resources.

[0043] The whole-process intelligent case management method for breast cancer patients includes: S1: The patient first registers at the case management port on the mobile terminal. After registration, personal health data is entered; S2: The case management port conducts a disease assessment and diagnosis on the patient's personal health data; S3: The case management port formulates a treatment plan for the patient according to the disease assessment and diagnosis results; S4: The patient opens the case management port on the mobile terminal to view and execute the treatment plan; S5: The patient records the feedback information during the treatment process in a timely manner, and the case management port generates rehabilitation suggestions according to the feedback information; S6: The case management port transmits the rehabilitation suggestions and feedback records to the remote consultation platform for expert consultation. The remote consultation platform then transmits the consultation records to the case management port, and the case management port generates the results of the monitoring and treatment of the consultation records.

[0044] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0045] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. The intelligent case management system for breast cancer patients is characterized by: include: Patient information collection unit, used for: The patient registers the case management port on the mobile terminal, enters the health data after registration, and pre-processes the data after the health data is entered. After the data is pre-processed, the target health data is obtained; Data Brain Chip Diagnostic Unit, used for: Use FFCA technology to build a disease assessment model for target health data, combine the constructed disease assessment model with the brain-like chip and perform intelligent analysis and diagnosis. After the intelligent analysis and diagnosis is completed, the patient's diagnostic data is obtained; Intervention Planning Unit to: Formulate intervention plans based on patient diagnostic data, and convert the formulated intervention plans into visual data. After the visual data conversion is completed, the patient treatment plan is obtained; Intervention Program Coordination Unit to: The patient can view the patient's treatment plan in the case management port, and perform treatment according to the content of the patient's treatment plan. In addition, the case management port can assist in medication according to the treatment content of the patient's treatment plan; The data brain chip diagnostic unit is also used for: Confirming feature data in the target health data, and performing context-aware analysis on the confirmed feature data, wherein the context-aware analysis includes time context and environmental context; The feature data after context-aware analysis is used to build a disease assessment model using FFCA technology; The disease assessment model is constructed by first using FFCA technology to perform cluster analysis on the feature data after context-aware analysis; After cluster analysis, a recurrent neural network was used to construct a disease assessment model, and the constructed disease assessment model was optimized and verified.

2. The intelligent case management system for breast cancer patients according to claim 1 is characterized in that: The data brain chip diagnostic unit optimizes and verifies the constructed disease assessment model, including: Extracting verification data corresponding to multiple different disease characteristics from the verification data set, and obtaining verification training data and verification result data from each verification data; Based on the impact of different disease characteristics on breast cancer patients, the corresponding validation weights of validation training data are set; The disease assessment model is verified based on the verification training data and the verification result data to obtain the deviation and variance of the model under each disease characteristic; Based on the deviation and variance of the model under each disease characteristic, the model evaluation value K of the disease assessment model is calculated according to the following formula; Where n represents the number of disease characteristics, represents the verification weight of the i-th disease feature, represents the deviation value of the i-th disease feature, represents the variance value of the i-th disease characteristic, represents the standard deviation value, represents the standard deviation value, represents a constant; Determining whether the model evaluation value is greater than a preset evaluation value; If so, determining that the condition assessment model does not need to be optimized; Otherwise, determining that the condition assessment model needs to be optimized; Based on the model evaluation value, the optimization weight F of the condition assessment model is determined according to the following formula; in, represents the average standard weight, Indicates the preset evaluation value; The optimization scheme corresponding to the optimization weight is obtained from a preset optimization scheme set to optimize the condition assessment model.

3. The intelligent case management system for breast cancer patients according to claim 2 is characterized in that: The data brain chip diagnostic unit is also used for: Adapt the optimized and verified disease assessment model to the interface of the brain-like chip; After the adaptation process is completed, the optimized and verified disease assessment model will be deployed on the brain-like chip; The brain-like chip uses pattern recognition and neural network algorithms to diagnose the received disease assessment model in real time; The diagnosis includes the severity, type, stage of development and complications involved in the patient’s condition; After the diagnosis is completed, the patient's diagnostic data is obtained.

4. The intelligent case management system for breast cancer patients according to claim 3 is characterized in that: The patient information collection unit is further used for: The patient uses a mobile terminal to scan the code on the case management port to register. After registration, the patient logs in to the case management port and enters personal health data; Among them, personal health data includes the patient's basic information, medical history information, physiological indicators, biochemical indicators, historical treatment information, living habits, psychological state, current physical symptoms and medication use; Preprocess the entered health data, including data cleaning, data standardization, data conversion, feature extraction and data integration; After data preprocessing is completed, the target health data is obtained.

5. The intelligent case management system for breast cancer patients according to claim 4, characterized in that: After cluster analysis in the data brain chip diagnosis unit, a recurrent neural network is used to construct a disease assessment model, including: An initial model building unit is used to obtain feature data after cluster analysis, and perform feature selection and feature conversion on the feature data based on multiple disease assessment requirements to obtain multiple target feature sets, and train the multiple target feature sets based on a recurrent neural network to obtain multiple initial assessment models; A model integration unit is used to adjust and verify the hyperparameters of the multiple initial evaluation models, obtain multiple reference evaluation models corresponding to the optimal hyperparameters, obtain the prediction results of the multiple reference evaluation models, and train the prediction results based on a recurrent neural network to obtain a comprehensive evaluation model; A model comparison unit, used to obtain model structure differences between the comprehensive evaluation model and multiple reference evaluation models, and determine whether the model structure differences are all within a preset difference range; If so, the comprehensive evaluation model is used as the target evaluation model; Otherwise, the model structure of the comprehensive evaluation model is modified based on the model structure difference, and the target evaluation model is obtained according to the modification result; The model simplification unit is used to simplify the target assessment model based on the model generalization capability requirements to obtain a final disease assessment model.

6. The intelligent case management system for breast cancer patients according to claim 5, characterized in that: The intervention program formulation unit is also used to: Before formulating an intervention plan, the patient’s diagnostic data should be analyzed in depth; After in-depth analysis, the patient's symptom characteristics, risk assessment information and individual characteristics in the patient's diagnostic data were obtained; Construct a treatment plan framework based on the patient's diagnostic data, which includes drug therapy, surgical treatment, radiotherapy, chemotherapy and lifestyle intervention; Refine the treatment plan based on the treatment plan framework and in-depth analysis of patient diagnostic data, including specific steps, timetable and expected goals of treatment; Then, the drug type, dosage, administration time and administration method are confirmed based on the patient's drug use and treatment response; Annotate treatment side effects based on detailed treatment regimen and patient medication selection; The final treatment plan is converted into a visual form of charts and timelines for presentation, and the patient's treatment plan, treatment time, medication status, and side effect notes are obtained after presentation; Label the treatment plan in visual form as the patient's treatment plan.

7. The intelligent case management system for breast cancer patients according to claim 6, characterized in that: The Intervention Program Coordination Unit is also responsible for: After logging into the case management portal on a mobile terminal, the patient can view the patient's treatment plan; The patient receives treatment according to the treatment method and treatment time in the patient's treatment plan, and the patient will feedback the reaction and side effects to the case management port during the treatment process; At the same time, the case management port provides medication assistance reminders based on the type, dosage, administration time and administration method of the drug in the patient's treatment plan; The reminder method is to send the drug type, dosage, administration time and administration method to the patient's mobile terminal for reminder.

8. The intelligent case management system for breast cancer patients according to claim 7, characterized in that: It also includes a rehabilitation follow-up supervision unit for: When patients receive treatment according to the treatment plan, treatment feedback is recorded in real time. The case management port conducts rehabilitation assessment based on the feedback record, generates rehabilitation suggestions based on the rehabilitation assessment results, and displays the generated rehabilitation suggestions visually. Among them, during the treatment process, patients log in to the case management port through mobile terminals and input feedback information in real time; Feedback includes treatment implementation, symptoms or side effects, psychological status and impact on daily life, and unexpected events; The case management port receives the feedback information, and a rehabilitation assessment algorithm is built into the case management port, and the rehabilitation assessment algorithm performs rehabilitation assessment on the feedback information; The rehabilitation assessment process includes symptom analysis, side effect assessment, and treatment compliance assessment; Based on the results of the rehabilitation assessment, the case management portal generates personalized rehabilitation recommendations; Recovery recommendations include treatment modification, side effect management, lifestyle adjustments, and psychological counseling; The rehabilitation suggestions are converted into visual form and then transmitted to the mobile terminal for display after the visual conversion.

9. The intelligent case management system for breast cancer patients according to claim 8, characterized in that: Also includes a remote monitoring consultation unit for: The case management port transmits the patient's feedback records and rehabilitation suggestions to the remote consultation platform for expert consultation, and performs monitoring and treatment based on the consultation results; Among them, the patient's feedback records and rehabilitation suggestions are summarized and the summarized data is encrypted; The case management portal logs into the remote consultation platform via a secure network connection; The encrypted summary data is uploaded to the remote consultation platform, wherein the case management port confirms the completion of data transmission and receives confirmation information from the remote consultation platform; After the remote consultation platform receives the data, the expert logs in to the remote consultation platform to view the patient's feedback records and rehabilitation suggestions; Professional analysis will be conducted based on the feedback records and rehabilitation suggestions, and consultation opinions will be obtained after professional analysis; The remote consultation platform transmits the consultation opinions to the case management port, which organizes the consultation opinions into documents, and the case management port monitors the patients according to the documents; Custody management includes adjustment of treatment regimen and enhanced monitoring measures.

10. A method for intelligent case management of breast cancer patients throughout the entire process, applied in the intelligent case management system of breast cancer patients throughout the entire process as claimed in claim 9, characterized in that: include: S1: The patient first registers the case management port on the mobile terminal and enters personal health data after registration; S2: The case management port uses the patient’s personal health data to assess and diagnose the condition; S3: The case management port formulates a treatment plan for the patient based on the condition assessment and diagnosis results; S4: The patient opens the case management port on the mobile terminal to view and execute the treatment plan; S5: The patient records the feedback information during the treatment process in a timely manner, and the case management port generates rehabilitation suggestions based on the feedback information; S6: The case management port transmits the rehabilitation suggestions and feedback records to the remote consultation platform for expert consultation. The remote consultation platform transmits the consultation records to the case management port, and the case management port generates monitoring processing results for the consultation records.

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