Intelligent follow-up system for rehabilitation management of integrated traditional Chinese and western medicine after inguinal hernia surgery

Abstract

The present application relates to the technical field of healthcare informatics, in particular to an intelligent follow-up system for postoperative rehabilitation management of inguinal hernia combining traditional Chinese and western medicine, which determines and updates a basic physiological index vector according to the size of each postoperative inguinal hernia patient's disease condition evaluation index and each operation degree parameter value, combines the basic physiological index vector to perform clustering operation on all postoperative inguinal hernia patients, in each cluster, according to the difference of the quantification value of the same disease condition performance of different postoperative inguinal hernia patients in all follow-ups and the difference of disease condition comprehensive feature performance, combines the distance between the basic physiological index vectors to determine the disease condition rehabilitation trajectory fitness of each postoperative inguinal hernia patient as an auxiliary rehabilitation judgment index to manage the follow-up data of postoperative inguinal hernia patients. The present application can improve the management effect of postoperative rehabilitation follow-up data of inguinal hernia patients.

Description

Technical Field

[0001] This invention relates to the field of healthcare informatics technology, specifically to an intelligent follow-up system for postoperative rehabilitation management of inguinal hernia using a combination of traditional Chinese and Western medicine. Background Technology

[0002] Inguinal hernia is one of the most common diseases in general surgery, and its surgical treatment, especially tension-free repair, has become the standard procedure. With the popularization of minimally invasive techniques such as laparoscopy and robotic surgery, surgical trauma has been continuously reduced, patient hospital stays have been significantly shortened, and many surgeries are even performed in day surgery centers. However, the success of the surgery does not depend solely on the skillful intraoperative technique. Postoperative rehabilitation and long-term follow-up are key to ensuring treatment effectiveness, preventing complications (such as chronic pain, seroma, and infection) and recurrence, and improving patients' quality of life. At the same time, the management of postoperative follow-up data to generate postoperative rehabilitation plans has great reference value for the postoperative rehabilitation treatment of new patients.

[0003] In the data processing stage before classifying rehabilitation training for inguinal hernia patients to provide personalized recommendations for postoperative recovery of inguinal hernia patients, it is necessary to classify and process the symptoms and postoperative recovery process of patients after inguinal hernia surgery. In addition, relevant data from traditional Chinese medicine and Western medicine should be analyzed as data parameters in the same database to improve the management effectiveness of follow-up records.

[0004] Existing problem: When following up on the postoperative rehabilitation effects of inguinal hernia patients, the follow-up intervals are inconsistent and relatively long. When patients describe their postoperative condition, they often focus on recent obvious symptoms, such as: "I felt obvious pain a week ago, but I haven't felt obvious pain recently." They may then describe no obvious pain as their current condition. This can lead to doctors misjudging the actual severity of the patient's condition when analyzing the symptoms based on the patient's description, affecting the patient's postoperative rehabilitation effect. As a result, the postoperative rehabilitation management data of inguinal hernia patients is not of research value. Summary of the Invention

[0005] This invention provides an intelligent follow-up system for rehabilitation management combining traditional Chinese and Western medicine after inguinal hernia surgery, in order to solve existing problems.

[0006] The intelligent follow-up system for postoperative rehabilitation management of inguinal hernia using integrated traditional Chinese and Western medicine, as described in this invention, adopts the following technical solution: One embodiment of the present invention provides an intelligent follow-up system for rehabilitation management combining traditional Chinese and Western medicine after inguinal hernia surgery. The system includes the following modules: Follow-up data acquisition module: used to obtain the basic physiological index vector, disease evaluation index, surgical degree parameter value, and quantitative value of each disease manifestation corresponding to each follow-up for each patient after inguinal hernia surgery. The patient classification module is used to determine the comprehensive characteristics of the disease based on the magnitude of the disease evaluation indicators and the parameters of each surgical degree; and to perform clustering operations on all patients after inguinal hernia surgery based on the deviation between the basic physiological index vectors after surgery and the comprehensive characteristics of the disease, thereby determining at least one cluster. The auxiliary rehabilitation judgment index analysis module is used to determine the degree of consistency of the disease rehabilitation trajectory of each patient after inguinal hernia surgery in each cluster, based on the differences in the quantitative values ​​of the same disease manifestation in all follow-ups of different patients after inguinal hernia surgery, as well as the differences in the comprehensive characteristics of the disease, combined with the distance between the basic physiological index vectors. Follow-up data management module: Used to manage follow-up data of patients after inguinal hernia surgery, using the degree of consistency between the recovery trajectory of the aforementioned disease and the recovery trajectory as an auxiliary indicator for judging recovery.

[0007] Furthermore, the process of determining the comprehensive characteristics of the disease includes: For each patient who has undergone inguinal hernia surgery, the mean of all surgical severity parameters is recorded as the surgical quantitative value. The product of the surgical quantitative value and the disease evaluation index is normalized to determine the comprehensive characteristics of the disease.

[0008] Furthermore, the process of determining the degree of agreement between the recovery trajectory and the patient's condition after inguinal hernia surgery includes: Within each cluster, based on the differences in the quantitative values ​​of the same symptom manifestation in all follow-up visits among different patients after inguinal hernia surgery, as well as the differences in the comprehensive characteristics of the symptom manifestation, the comprehensive pathological manifestation difference parameter for each patient after inguinal hernia surgery is determined; based on the differences in the comprehensive pathological manifestation difference parameter among different patients after inguinal hernia surgery, as well as the distance between the basic physiological index vectors, the degree of agreement on the symptom recovery trajectory for each patient after inguinal hernia surgery is determined.

[0009] Furthermore, the process of determining the comprehensive pathological differences in each patient after inguinal hernia surgery includes: Interpolation fitting was performed on the quantitative values ​​of the same symptom in all follow-up visits for each patient after inguinal hernia surgery to determine the time-series change curve of each symptom in each patient after inguinal hernia surgery. Global polynomial fitting was performed on the time-series change curves of the same symptom in all patients after inguinal hernia surgery in each cluster to determine the typical change curve of each symptom in each cluster. Record any symptom as the reference symptom. Based on the difference between the time-series change curve of the reference symptom presentation of each postoperative inguinal hernia patient in each cluster and the corresponding typical change curve, the degree of difference in the reference symptom presentation of each postoperative inguinal hernia patient is determined as a parameter. Based on the differences in the temporal change curves of the reference disease manifestations of different patients after inguinal hernia surgery in each cluster, as well as the differences in the comprehensive characteristics of the disease, the difference adjustment coefficient for the reference disease manifestations of each patient after inguinal hernia surgery was determined. The difference adjustment coefficient is used to correct the difference degree parameter to determine the comprehensive pathological difference parameter for each patient after inguinal hernia surgery.

[0010] Furthermore, the process of determining the degree of agreement between the comprehensive pathological manifestations and the distances between the basic physiological index vectors of different inguinal hernia patients after surgery includes: The first anastomosis value for each inguinal hernia patient is determined based on the distance between the basic physiological index vectors of different inguinal hernia patients in each cluster. Based on the differences in comprehensive pathological manifestations among patients after inguinal hernia surgery in each cluster, the second anastomosis value for each patient after inguinal hernia surgery was determined. The degree of agreement between the first and second anastomosis values ​​of each patient after inguinal hernia surgery is determined.

[0011] Furthermore, the process of determining the difference adjustment coefficient for the reference symptom presentation of each postoperative inguinal hernia patient includes: In each cluster, any patient who has undergone surgery for inguinal hernia is designated as the target patient, and all other patients who have undergone surgery for inguinal hernia are designated as reference patients. Using the DTW algorithm, the DTW distance value between the time-series change curve of the reference symptom performance of the target patient and the time-series change curve of the reference symptom performance of each reference patient is obtained. Among the DTW distance values ​​between the time-series change curve of the reference symptom performance of the target patient and the time-series change curve of the reference symptom performance of all reference patients, all reference patients whose normalized DTW distance value is less than the preset similarity threshold are recorded as the main reference patients. Calculate the standard deviation of the comprehensive symptom characteristics of all primary reference patients to determine the reference dispersion; determine the reference difference value based on the absolute value of the difference between the mean of the comprehensive symptom characteristics of all primary reference patients and the comprehensive symptom characteristics of the target patient; and determine the difference adjustment coefficient of the target patient in the reference symptom characteristics by negatively normalizing the ratio between the reference difference value and the reference dispersion.

[0012] Furthermore, the process of using the difference adjustment coefficient to correct the difference degree parameter and determining the comprehensive pathological manifestation difference parameter for each inguinal hernia postoperative patient includes: The product of the difference adjustment coefficient and the difference degree parameter for each postoperative inguinal hernia patient in terms of the reference symptoms is recorded as the corrected difference parameter for each postoperative inguinal hernia patient in terms of the reference symptoms. The comprehensive pathological manifestation difference parameter for each patient after inguinal hernia surgery was determined based on the mean of the adjusted difference parameters across all disease manifestations.

[0013] Furthermore, the process of determining the first anastomosis value for each patient after inguinal hernia surgery includes: In each cluster, the average vector of the basic physiological indicators of all patients after inguinal hernia surgery is first obtained, and then the Euclidean distance between the average vector and the basic physiological indicator vector of each patient after inguinal hernia surgery is obtained. The inversely proportional normalized value of the Euclidean distance is recorded as the first concordance value of each patient after inguinal hernia surgery.

[0014] Furthermore, the process of determining the second anastomosis value for each patient after inguinal hernia surgery includes: Within each cluster, the comprehensive difference value between each inguinal hernia patient and any other inguinal hernia patient is determined based on the absolute value of the difference between the comprehensive pathological manifestation difference parameter of each inguinal hernia patient and any other inguinal hernia patient. The mean of the comprehensive difference values ​​of each inguinal hernia patient and all other inguinal hernia patients is then negatively correlated and normalized to determine the second anastomosis value for each inguinal hernia patient.

[0015] Furthermore, the process of determining the degree of agreement on the recovery trajectory of each inguinal hernia patient based on the magnitude of the first and second anastomosis values ​​includes: The average of the first and second anastomosis values ​​for each patient after inguinal hernia surgery is recorded as the degree of agreement of the patient's recovery trajectory after inguinal hernia surgery.

[0016] The beneficial effects of the technical solution of the present invention are: In this embodiment of the invention, based on the evaluation indicators of each inguinal hernia postoperative patient and the values ​​of each surgical severity parameter, the comprehensive characteristics of the disease are determined. These comprehensive characteristics are added to the basic physiological indicator vector, and the updated basic physiological indicator vector is determined. Based on the distance between the updated basic physiological indicator vectors, all inguinal hernia postoperative patients are clustered to determine at least one cluster. Within each cluster, based on the differences in the quantitative values ​​of the same disease manifestation across all follow-up visits and the differences in the comprehensive characteristics of the disease, combined with the distance between the basic physiological indicator vectors, the degree of alignment of the disease recovery trajectory for each inguinal hernia postoperative patient is determined. This degree of alignment is used as an auxiliary indicator for managing the follow-up data of inguinal hernia postoperative patients. Thus, this invention significantly improves the quality of follow-up data through dual optimization of "similar patient clustering" and "multidimensional recovery trajectory alignment assessment." Intelligent grouping based on patient surgical conditions and basic physiological indicators achieves "comparison within the same category," reducing the interference of individual differences on the evaluation of recovery curves. Secondly, by integrating group deviation with individual real-time physiological status to calculate the consistency of rehabilitation trajectory, abnormal data caused by narrative bias or actual pathology can be identified, thereby screening out high-value abnormal warnings and reliable trends, making rehabilitation assessment more objective, and improving the management effectiveness of postoperative rehabilitation follow-up data for inguinal hernia patients. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a module of an intelligent follow-up system for postoperative rehabilitation management of inguinal hernia using integrated traditional Chinese and Western medicine, according to the present invention. Figure 2 A flowchart for managing follow-up data of patients after inguinal hernia surgery. Detailed Implementation

[0019] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an intelligent follow-up system for integrated traditional Chinese and Western medicine rehabilitation management after inguinal hernia surgery proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0021] The following description, in conjunction with the accompanying drawings, details the specific scheme of the intelligent follow-up system for postoperative rehabilitation management of inguinal hernia using integrated traditional Chinese and Western medicine.

[0022] Please see Figure 1 The diagram illustrates a module flowchart of an intelligent follow-up system for integrated traditional Chinese and Western medicine rehabilitation management after inguinal hernia surgery, provided by an embodiment of the present invention. The system includes the following modules: Follow-up data collection module 101: This module is used to obtain the basic physiological index vector, disease evaluation index, parameter value of each surgical degree, and quantitative value of each disease manifestation corresponding to each follow-up for each patient after inguinal hernia surgery.

[0023] In the hospital's database, for each patient who has undergone inguinal hernia surgery, the basic physiological indicators from the patient's medical records at the time of discharge are first collected to form a basic physiological indicator vector, along with the patient's symptom evaluation indicators given by the attending physician.

[0024] Among them, the symptom evaluation index is a data value obtained through medical scoring systems such as the NYHA classification. Medical scoring systems such as the NYHA classification are common knowledge and are standard assessment tools that are widely used and publicly available in clinical practice.

[0025] It should be noted that each basic physiological indicator in the basic physiological indicator vector should be an indicator that has been recorded for all patients after inguinal hernia surgery. Specifically, the basic physiological indicator vector includes: heart rate, blood pressure, blood glucose, BMI (modern medical indicator), and core TCM indicators, among which the core TCM indicators include: tongue coating thickness quantification value (score from 0 to 10), pulse strength value (score from 0 to 10), and complexion score (score from 0 to 10). This ensures the consistency of the vector structure, guarantees data comparability, and facilitates clinical promotion and standardization. Furthermore, the min-max normalization method is used to normalize the same basic physiological indicator in the basic physiological indicator vector of all patients after inguinal hernia surgery to an interval. Internally, it ensures the uniformity of dimensions for different basic physiological indicators in the basic physiological indicator vector.

[0026] In this embodiment, a bias method is used to introduce a very small positive number (e.g., 0.0001) into the min-max normalization method to avoid the normalization value being 0. Both the min-max normalization method and the bias method are well-known techniques, and the specific methods will not be described here.

[0027] Then, the surgical severity parameters of each inguinal hernia surgery patient were collected postoperatively. In this embodiment, wound size, surgical depth, and total blood loss are used, but these can be adjusted according to the specific implementation environment. The minimum-maximum normalization method was used to normalize the same surgical severity parameter value for all inguinal hernia surgery patients to a range. Internally, ensure the dimensional uniformity of parameter values ​​for different surgical procedures.

[0028] Then, after each patient was discharged from the hospital following surgery for inguinal hernia, quantitative values ​​of each symptom were collected for each follow-up visit.

[0029] It should be noted that in this embodiment, the recovery effect of inguinal hernia patients at different recovery stages after surgery is followed up by direct observation of the affected area and a table of symptom manifestations. The follow-up data is uploaded to the hospital system platform and stored in the database. Each follow-up involves the patient coming to the hospital for examination or data collection of the affected surgical area and areas reflecting the patient's current vital signs through methods such as video recording. Subsequently, the patient's symptom manifestations during the recovery period are recorded using a consultation or a table. The symptom manifestations included in each follow-up include: pain level, fatigue level, infection level, etc. The severity of each symptom manifestation is ranked from best to worst as good, mild, moderate, severe, and worsening, with corresponding quantitative values ​​of 1, 2, 3, 4, and 5, respectively. Each follow-up also corresponds to a timestamp.

[0030] It should be further noted that this embodiment targets inguinal hernia surgery patients who have been discharged and have undergone three or more follow-up visits, and the sample size of inguinal hernia surgery patients is at least 100. During the follow-up data collection process, the follow-up data includes not only in-hospital check-ups but also self-assessment data uploaded daily or weekly by patients via smart terminals (images of the surgical area, completed electronic symptom questionnaires), thus ensuring a large amount of data support for subsequent follow-up data analysis.

[0031] Patient classification module 102: This module is used to determine the comprehensive characteristics of the disease based on the magnitude of the disease evaluation index and the value of each surgical degree parameter; and to perform clustering operations on all patients after inguinal hernia surgery based on the deviation between the basic physiological index vector after surgery and the comprehensive characteristics of the disease, thereby determining at least one cluster.

[0032] It should be noted that an inguinal hernia is a mass that protrudes through a weak or defective area of ​​the abdominal wall in the groin region, forming a lump. Postoperative suturing is required, and there is a risk of recurrence. Postoperative outcomes vary depending on the patient's surgical condition and recovery environment. To ensure effective recovery, follow-up is necessary to develop a rehabilitation plan and a general strategy for each patient based on data. However, patients often report significant recent improvements at different recovery stages, leading to low objectivity in long-term feedback and affecting the reference value of the plan. Therefore, it is necessary to compare the postoperative recovery processes of similar patients to select those with reference value as the basis for the rehabilitation plan.

[0033] It is important to further clarify that the postoperative recovery outcome for inguinal hernia patients depends not only on the skillful surgical technique during the operation, but also on postoperative rehabilitation and long-term follow-up. These are crucial for ensuring treatment effectiveness, preventing complications (such as chronic pain, seroma, and infection) and recurrence, and improving the patient's quality of life. Postoperative recovery is influenced by various physical indicators, such as: unstable heart rate and blood pressure affecting organ perfusion and wound blood supply; poor nutritional status delaying wound healing; and poor blood sugar control in diabetic patients increasing the risk of infection. All of these factors affect the recovery process. Therefore, due to individual differences in patient presentation, when classifying postoperative recovery processes, it is essential to use the recovery processes of patients with similar physical signs as a reference, as this approach is more reliable and minimizes the impact of different physical parameters on the construction of postoperative recovery plans. Therefore, when processing postoperative recovery follow-up data for various inguinal hernia patients, it is necessary to first classify the similarities in patient presentations within the patient group.

[0034] Therefore, the comprehensive characteristics of the disease are determined first by the evaluation indicators of each patient after inguinal hernia surgery and the values ​​of each surgical degree parameter.

[0035] It should be noted that postoperative recovery is influenced not only by the patient's baseline physiological indicators but also by the presentation of the disease and the surgical procedure itself. Factors such as wound size and the severity of the affected area significantly impact recovery; larger wounds and more severe lesions result in slower recovery. Therefore, when clustering patients based on their pre-operative condition similarity, it is necessary to consider the comprehensive characteristics of their pathological manifestations. In analyzing patient symptoms, the large volume of pathological parameters and the difficulty in standardizing quantification lead to slower data processing and lower accuracy due to the high data dimensionality. Therefore, a comprehensive characteristic profile of the patient's condition is constructed based on the evaluation indicators of the pathological manifestations as assessed by the attending physician within multidimensional data, combined with the quantified degree of surgical procedures performed. This comprehensive profile serves as the basis for classifying the patient's baseline pathological characteristics.

[0036] Therefore, based on the deviation between the baseline physiological index vectors and the comprehensive characteristics of the disease in different inguinal hernia patients after surgery, clustering was performed on all inguinal hernia patients to determine at least one cluster. Specifically: For each patient who has undergone inguinal hernia surgery, the comprehensive characteristics of the disease are added to the basic physiological index vector to determine the updated basic physiological index vector.

[0037] For example: the Updated baseline physiological parameters vector for patients after groin hernia surgery ,in, For the first The comprehensive characteristics of symptoms in patients after inguinal hernia surgery. For the first The basic physiological index vector of patients after inguinal hernia surgery.

[0038] Using the Euclidean distance between the updated baseline physiological index vectors of any two post-operative inguinal hernia patients as the clustering distance, a hierarchical clustering algorithm is used to cluster all post-operative inguinal hernia patients, identifying at least one cluster. Patients in each cluster have similar pathological manifestations.

[0039] Among them, the hierarchical clustering algorithm is a well-known technique, and the specific method will not be introduced here.

[0040] It should be noted that, in addition to being directly affected by the disease itself, a patient's postoperative recovery is also influenced by their physical condition (basic physiological indicators). Therefore, when screening for similarity in postoperative recovery plans for inguinal hernia patients as a reference for new patients, it is necessary to combine the patient's physical condition (basic physiological indicators) and the overall manifestations of the disease to conduct an overall similarity analysis of the patient's disease stage. Based on this, an updated basic physiological indicator vector is constructed by combining the patient's basic physiological indicators with the overall characteristics of the disease, serving as the data basis for analyzing the postoperative recovery process of inguinal hernia patients.

[0041] It should be further noted that if the number of post-operative inguinal hernia patients in a cluster is less than 5, then all post-operative inguinal hernia patients in that cluster are considered special patients and directly marked as abnormal patients, and will not be further analyzed. If the number of post-operative inguinal hernia patients in a cluster is greater than or equal to 5, then the post-operative inguinal hernia patients in that cluster will be further analyzed. In this embodiment, the clustering threshold in the adaptive hierarchical clustering algorithm ensures that the number of clusters to be analyzed is at least one, which is a well-known technique.

[0042] Module 103 for Assisted Rehabilitation Assessment Indicators: This module is used to determine the degree of agreement between the recovery trajectory of each inguinal hernia patient and the symptom of the disease in each cluster, based on the differences in the quantitative values ​​of the same symptom in all follow-up visits of different patients after inguinal hernia surgery, the differences in the comprehensive characteristics of the disease, and the distance between the vectors of basic physiological indicators.

[0043] It should be noted that postoperative follow-up for inguinal hernia patients can be conducted by observing wound healing, such as the presence of redness and swelling, oozing, and the degree of pain, to analyze the patient's recovery effect. For example, if, within one week after surgery, follow-up reveals that the area of ​​redness and swelling gradually decreases, oozing reduces, and pain changes from severe to mild, this indicates good wound healing and significant short-term treatment effectiveness. Simultaneously, it's important to understand the patient's early recovery of mobility, such as the ability to walk normally and perform simple movements like squatting, to determine if the surgery's impact on the patient's daily activities is within expectations. However, different recovery periods often reflect more recent and obvious results, leading to lower objectivity in feedback over longer periods. Therefore, it is necessary to conduct a recovery trajectory consistency analysis based on the differences in symptom presentation within a patient group with similar symptoms over the course of the illness.

[0044] It should be further explained that when analyzing the rationality of a patient's symptoms at a certain moment, it is necessary not only to pay attention to the differences between the patient's symptoms and those of the general population, but also to understand the differences in the patient's physiological indicators at the current stage and in the early postoperative period. The more normal the patient's physiological indicators are, the higher the degree of consistency between the patient's pathological manifestations and the recovery trajectory.

[0045] Therefore, in this embodiment, based on the differences in the quantitative values ​​of the same symptom manifestations of different inguinal hernia patients in each cluster across all follow-ups, as well as the differences in the comprehensive symptom characteristics, and combined with the distance between the basic physiological index vectors, the degree of agreement on the symptom recovery trajectory of each inguinal hernia patient is determined.

[0046] Follow-up Data Management Module 104: This module is used to manage follow-up data of patients after inguinal hernia surgery, using the degree of consistency between the recovery trajectory of the aforementioned condition as an auxiliary indicator for judging recovery.

[0047] For each patient who has undergone inguinal hernia surgery, the degree of alignment between the symptoms and the recovery trajectory is used as an auxiliary indicator for assessing recovery. This is combined with the patient's basic physiological indicators, symptoms evaluation indicators, all surgical degree parameters, and the quantitative values ​​of all symptoms observed in all follow-ups. This allows the attending physician to mark the patient as normal or abnormal.

[0048] In the hospital's database, all relevant data for each inguinal hernia surgery patient can be organized into a separate document. Documents of all inguinal hernia surgery patients with the same label (normal or abnormal) in each cluster are integrated and stored in the same file to facilitate subsequent data analysis, model training, or result display, thereby completing the follow-up data management for inguinal hernia patients' postoperative rehabilitation.

[0049] It should be noted that in this embodiment, the recovery trend of the disease is constructed by using the Chinese and Western medicine disease parameters of the patient at different follow-up times, such as wound healing effect, pain level, physical performance (nutritional status), and abnormal states (such as: the disease continues to recover well, but the recovery is poor at a certain stage). Then, the recovery effect of the patient group with similar disease performance is analyzed to determine the degree of consistency of the recovery trajectory, and the patient is marked as abnormal based on the analysis results of the degree of consistency of the recovery trajectory.

[0050] In this embodiment, the flowchart for follow-up data management of patients after inguinal hernia surgery is as follows: Figure 2 As shown.

[0051] Preferably, in some possible implementations of the embodiments of the present invention, for each patient after inguinal hernia surgery, the mean value of all surgical degree parameters is recorded as the surgical quantification value, the product of the surgical quantification value and the disease evaluation index is calculated, and the normalized value of the product is recorded as the comprehensive characteristic manifestation of the disease.

[0052] It should be noted that each surgical severity parameter value has been normalized to a range. Therefore, the surgical quantification value is within the range. Dimensionless data values ​​within a given range are used to adjust the symptom evaluation indicators to obtain a comprehensive symptom profile. A higher comprehensive symptom profile indicates greater surgical difficulty, more severe symptoms, and slower postoperative recovery. Since each inguinal hernia surgery patient corresponds to a product of a surgical quantification value and a symptom evaluation indicator, the min-max normalization method is used to normalize the product of the surgical quantification value and the symptom evaluation indicator for all inguinal hernia surgery patients to a range. Inside.

[0053] Preferably, in some possible implementations of the embodiments of the present invention, in each cluster, based on the differences in the quantitative values ​​of the same symptom manifestations in all follow-up visits of different inguinal hernia patients, as well as the differences in the comprehensive symptom characteristics, the comprehensive pathological manifestation difference parameters of each inguinal hernia patient are determined. Based on the differences in the comprehensive pathological manifestation difference parameters of different inguinal hernia patients, as well as the distance between the basic physiological index vectors, the degree of agreement of the symptom recovery trajectory of each inguinal hernia patient is determined.

[0054] Preferably, in some possible implementations of the embodiments of the present invention, a Savitzky-Golay filter is used to interpolate and fit the quantitative values ​​of the same symptom manifestation for each patient after inguinal hernia surgery in all follow-up visits, thereby determining the time-series change curve of each symptom manifestation for each patient after inguinal hernia surgery.

[0055] The Savitzky-Golay filter is a well-known technique, and its specific method will not be described here.

[0056] It should be noted that the follow-up time may vary among patients, especially over long periods, where the interval between follow-up periods can differ by a week or several weeks. This can lead to time discrepancies affecting the comparative relationships when performing trend similarity analysis based on the symptom manifestations obtained during the follow-up period. To address the issue of inconsistent follow-up intervals (e.g., some patients have an interval of 3 days, others 7 days), this embodiment uses a Savitzky-Golay filter for interpolation fitting to fill in and map the discrete follow-up data to a unified standard time node (e.g., day 3 after discharge, day 7, etc.). This facilitates subsequent horizontal comparisons within the same period, ensuring that the estimated values ​​at adjacent follow-up times are closer to the actual follow-up data values, avoiding the influence of fixed coefficients on the similarity of follow-up results. Furthermore, based on the estimated results and actual follow-up results at each adjacent follow-up time during the patient's follow-up period, a time-series curve of the symptom manifestations in the patient's follow-up data is constructed. Specifically: For each patient post-operatively undergoing inguinal hernia surgery, the time-series curves for each symptom are plotted, with time on the horizontal axis and the quantified value of each symptom on the vertical axis. The origin of the horizontal axis is the patient's discharge date, and the interval between discharge and each follow-up time stamp is used as the horizontal axis value for each follow-up. This ensures that the time axes of the time-series curves for each symptom are aligned for all post-operatively undergoing inguinal hernia surgery patients.

[0057] Global polynomial fitting was performed on the time-series variation curves of the same symptom in all patients after inguinal hernia surgery in each cluster to determine the typical variation curve of each symptom in each cluster.

[0058] Global polynomial fitting is a well-known technique, and its specific method will not be described here. In this embodiment, the time-series change curves of the same symptom in all patients after inguinal hernia surgery in each cluster are merged to obtain the typical change curve of each symptom corresponding to that cluster, which is used to characterize the overall change trend of the cluster (this type of patient group) in the symptom.

[0059] Record any symptom as the reference symptom.

[0060] Based on the difference between the time-series change curve of the reference symptom presentation for each patient after inguinal hernia surgery in each cluster and the typical change curve of the reference symptom presentation for the corresponding cluster, the parameter of the degree of difference in the reference symptom presentation for each patient after inguinal hernia surgery is determined.

[0061] It should be noted that: the time-series change curves of the reference symptom presentation for each post-operative inguinal hernia patient in each cluster are obtained. Typical change curves of reference disease manifestations corresponding to each cluster The difference is specifically: using wavelet transform on the curve With curve Multi-resolution analysis is performed to identify the differences between the two in different frequency bands, and the degree of difference in the difference frequency band region is further extracted. This is a difference frequency band identification and feature extraction method based on wavelet multi-resolution analysis, which has been widely used in signal processing, pattern recognition and medical data analysis. It is a conventional signal analysis method known to those skilled in the art.

[0062] Based on the differences in the temporal variation curves of the reference symptoms among different postoperative inguinal hernia patients in each cluster, as well as the differences in the comprehensive characteristics of the symptoms, the difference adjustment coefficient for the reference symptoms of each postoperative inguinal hernia patient was determined.

[0063] The difference parameter was corrected by adjusting the difference in the reference symptoms for each patient after inguinal hernia surgery, and the overall pathological difference parameter for each patient after inguinal hernia surgery was determined.

[0064] It should be noted that due to differences in patients' baseline physiological parameters, symptoms, and specific surgical procedures—for example, deeper surgical procedures generally result in longer recovery periods—and even within similar patient clusters, individual patient presentations can vary. Therefore, when analyzing patient symptoms, it is necessary to consider the specific manifestations of each patient's condition. Consequently, the analysis of the obtained difference parameters needs to minimize the influence of physical signs between patients and eliminate inherent differences caused by variations in baseline physical signs and surgical circumstances. This requires determining a difference adjustment coefficient to correct the difference parameters and obtaining comprehensive pathological manifestation difference parameters.

[0065] Preferably, in some possible implementations of the embodiments of the present invention, in each cluster, any one postoperative inguinal hernia patient is designated as the target patient, and all postoperative inguinal hernia patients other than the target patient are designated as reference patients.

[0066] Using the DTW algorithm, the DTW distance value between the time-series change curve of the reference symptom performance of the target patient and the time-series change curve of the reference symptom performance of each reference patient is obtained. Among the DTW distance values ​​between the time-series change curve of the reference symptom performance of the target patient and the time-series change curve of the reference symptom performance of all reference patients, all reference patients whose normalized DTW distance value is less than the preset similarity threshold are recorded as the main reference patients.

[0067] It should be noted that the preset similarity threshold is 0.2, and this will be used as an example for explanation. The DTW (Dynamic Time Warping) algorithm is a well-known technique, and its specific method will not be described here. Using the min-max normalization method, the DTW distance values ​​between the time-series variation curves of the target patient's reference disease performance and the time-series variation curves of the reference disease performance of all reference patients are normalized to an interval. The smaller the DTW distance value, the more similar the two curves are. Therefore, all reference patients whose DTW distance value is less than the preset similarity threshold are recorded as primary reference patients, that is, patients who are highly similar to the target patient in terms of reference symptom presentation. In this embodiment, by adjusting the size of the preset similarity threshold, the number of primary reference patients is ensured to be at least 3.

[0068] Obtain the standard deviation of the comprehensive disease characteristics of all primary reference patients. Determine the reference dispersion and calculate the mean of the comprehensive disease characteristics of all main reference patients. Comprehensive characteristics of the target patient's condition absolute value of the difference Determine the reference difference value and calculate the ratio between the reference difference value and the reference dispersion. The inverse proportional normalized value of this ratio , denoted as the difference adjustment coefficient between the target patient and the reference disease manifestation.

[0069] in, It is an absolute value function. It is an exponential function with the natural constant as its base. Since it is a non-negative data value, for The inverse proportional normalized value, and its range is within the interval. Inside. To prevent due to A value of 0 results in a ratio This is not true. In this embodiment, the ratio is... Replace with ,in Let be a positive correction factor. The value is 0.01, and we will use this as an example for explanation.

[0070] It should be noted that: The larger the value, the greater the difference in the overall disease characteristics between the target patient and the main reference patient. The standard deviation... The smaller the value, the more similar the overall symptom characteristics of all the main reference patients, meaning the more reliable the overall symptom characteristics of the main reference patients. Therefore, using... right Make adjustments when A larger value indicates a significant difference between the target patient and the primary reference patient in their baseline physiological parameters and the specific surgical procedures. This difference leads to a greater degree of variation in the disease presentation. This is a reasonable deviation from the time-series curve of the disease presentation, rather than an abnormal deviation inherent in the time-series curve of the disease presentation in patients with special characteristics (e.g., advanced age, multiple underlying diseases) during the recovery process. In this case, the difference adjustment coefficient... It is close to 0, and is used to reduce the degree of difference parameter.

[0071] Preferably, in some possible implementations of the embodiments of the present invention, the product of the difference adjustment coefficient and the difference degree parameter of each postoperative inguinal hernia patient in the reference symptom presentation is recorded as the corrected difference parameter of each postoperative inguinal hernia patient in the reference symptom presentation.

[0072] The comprehensive pathological manifestation difference parameter for each patient after inguinal hernia surgery was determined based on the mean of the adjusted difference parameters across all disease manifestations.

[0073] It should be noted that: Therefore, by taking into account the differences in the comprehensive characteristics of the symptoms among patients who are highly similar in terms of the symptoms of the reference symptoms, the difference adjustment coefficient for the symptoms of the target patients in terms of the symptoms of the reference symptoms is determined, which is used to correct the difference parameter and ensure the reliability of the difference parameter of the comprehensive pathological manifestations.

[0074] Preferably, in some possible implementations of the embodiments of the present invention, the first anastomosis value of each inguinal hernia postoperative patient is determined based on the distance between the basic physiological index vectors of different inguinal hernia postoperative patients in each cluster.

[0075] Based on the differences in comprehensive pathological manifestation parameters among patients after inguinal hernia surgery in each cluster, the second anastomosis value for each patient after inguinal hernia surgery was determined.

[0076] The degree of agreement between the first and second anastomosis values ​​of each patient after inguinal hernia surgery is determined.

[0077] It should be noted that within each cluster, the greater the difference in the comprehensive pathological manifestation parameters between a patient who has undergone inguinal hernia surgery and other patients, the higher the degree of individualization (deviation from the overall trend) of the patient's disease trend, meaning the less consistent the disease recovery trajectory. Similarly, the greater the distance between the baseline physiological indicator vectors of a patient who has undergone inguinal hernia surgery and other patients, the more abnormal the patient's baseline physiological indicators, also indicating a less consistent disease recovery trajectory. Therefore, a joint abnormality index is constructed using the first and second concordance values ​​to represent the consistency of the disease recovery trajectory. The lower this value, the more the patient's recovery data deviates from the group trend, indicating unexpected recovery abnormalities (such as latent complications). Patients with low concordance need to be marked to prompt physicians to pay closer attention.

[0078] Preferably, in some possible implementations of the embodiments of the present invention, in each cluster, the average vector of the basic physiological index vectors of all patients after inguinal hernia surgery is first obtained, and then the Euclidean distance between the average vector and the basic physiological index vector of each patient after inguinal hernia surgery is obtained. The inversely proportional normalized value of the Euclidean distance is recorded as the first concordance value of each patient after inguinal hernia surgery.

[0079] It should be noted that the acquisition of the average vector is a well-known technique, and the specific method will not be described here. The average vector represents the standard basic physiological index vector corresponding to the cluster. Therefore, the greater the Euclidean distance between the basic physiological index vector and the average vector of each inguinal hernia postoperative patient, the less consistent the recovery trajectory is. Therefore, the inverse proportional normalized value of the Euclidean distance is taken as the first consistency value. The min-max normalization method is used to normalize the Euclidean distance between the average vector in each cluster and the basic physiological index vectors of all inguinal hernia postoperative patients to an interval. The difference between 1 and the normalized value of the Euclidean distance is used as the inverse proportional normalized value of the Euclidean distance.

[0080] Preferably, in some possible implementations of the embodiments of the present invention, in each cluster, based on the absolute value of the difference between the comprehensive pathological manifestation difference parameter of each inguinal hernia postoperative patient and the comprehensive pathological manifestation difference parameter of any other inguinal hernia postoperative patient, the comprehensive difference value between each inguinal hernia postoperative patient and any other inguinal hernia postoperative patient is determined, the mean of the comprehensive difference value between each inguinal hernia postoperative patient and all other inguinal hernia postoperative patients is obtained and recorded as the comprehensive difference mean, and the inverse proportional normalized value of the comprehensive difference mean is recorded as the second concordance value of each inguinal hernia postoperative patient.

[0081] It should be noted that each postoperative inguinal hernia patient corresponds to a mean of overall variance. The mean of overall variance for all postoperative inguinal hernia patients in each cluster is normalized to an interval using the min-max normalization method. Within this range, the difference between 1 and the normalized value of the mean of the comprehensive difference is used as the inverse normalized value of the mean of the comprehensive difference. The greater the difference in the comprehensive pathological manifestation parameters between each inguinal hernia surgery patient and other inguinal hernia surgery patients, that is, the larger the mean of the comprehensive difference, the less consistent the disease recovery trajectory is. Therefore, the inverse normalized value of the mean of the comprehensive difference is taken as the second consistency value.

[0082] Preferably, in some possible implementations of the embodiments of the present invention, the average of the first anastomosis value and the second anastomosis value of each inguinal hernia postoperative patient is recorded as the degree of consistency of the disease recovery trajectory of each inguinal hernia postoperative patient.

[0083] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0084] This invention is now complete.

[0085] In summary, in this embodiment of the invention, based on the magnitude of the symptom evaluation indicators and the values ​​of each surgical severity parameter for each inguinal hernia postoperative patient, the comprehensive symptom characteristics are determined. These comprehensive symptom characteristics are added to the basic physiological indicator vector, and the updated basic physiological indicator vector is determined. Based on the distance between the updated basic physiological indicator vectors, clustering is performed on all inguinal hernia postoperative patients to determine at least one cluster. Within each cluster, based on the differences in the quantitative values ​​of the same symptom manifestation across all follow-up visits for different inguinal hernia postoperative patients, as well as the differences in the comprehensive symptom characteristics, combined with the distance between the basic physiological indicator vectors, the symptom recovery trajectory conformity degree for each inguinal hernia postoperative patient is determined. This symptom recovery trajectory conformity degree is used as an auxiliary rehabilitation judgment indicator to manage the follow-up data of inguinal hernia postoperative patients. This invention can improve the management effect of postoperative rehabilitation follow-up data for inguinal hernia patients.

[0086] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent follow-up system for postoperative rehabilitation management of inguinal hernia combining traditional Chinese and Western medicine, characterized in that, The system includes the following modules: Follow-up data acquisition module: used to obtain the basic physiological index vector, disease evaluation index, surgical degree parameter value, and quantitative value of each disease manifestation corresponding to each follow-up for each patient after inguinal hernia surgery. Patient classification module: used to determine the comprehensive characteristics of the disease based on the magnitude of the disease evaluation indicators and the parameters of each surgical procedure. Based on the deviation between the basic physiological index vectors and the comprehensive characteristics of the disease in different patients after inguinal hernia surgery, clustering operations were performed on all patients after inguinal hernia surgery to determine at least one cluster. The auxiliary rehabilitation judgment index analysis module is used to determine the degree of consistency of the disease rehabilitation trajectory of each patient after inguinal hernia surgery in each cluster, based on the differences in the quantitative values ​​of the same disease manifestation in all follow-ups of different patients after inguinal hernia surgery, as well as the differences in the comprehensive characteristics of the disease, combined with the distance between the basic physiological index vectors. Follow-up data management module: Used to manage follow-up data of patients after inguinal hernia surgery, using the degree of consistency between the recovery trajectory of the aforementioned disease and the recovery trajectory as an auxiliary indicator for judging recovery.

2. The intelligent follow-up system for postoperative rehabilitation management of inguinal hernia according to the integration of traditional Chinese and Western medicine, according to claim 1, characterized in that, The process of determining the comprehensive characteristics of the disease includes: For each patient who has undergone inguinal hernia surgery, the mean of all surgical severity parameters is recorded as the surgical quantitative value. The product of the surgical quantitative value and the disease evaluation index is normalized to determine the comprehensive characteristics of the disease. 3.The intelligent follow-up system for postoperative rehabilitation management of inguinal hernia according to the integration of traditional Chinese and Western medicine of claim 1, characterized in that, The process of determining the consistency of the recovery trajectory of each patient after inguinal hernia surgery includes: Within each cluster, based on the differences in the quantitative values ​​of the same symptom manifestation in all follow-up visits among different patients after inguinal hernia surgery, as well as the differences in the comprehensive characteristics of the symptom manifestation, the comprehensive pathological manifestation difference parameters for each patient after inguinal hernia surgery are determined. Based on the differences in the comprehensive pathological manifestation difference parameters among different patients after inguinal hernia surgery, as well as the distance between the vectors of basic physiological indicators, the degree of agreement on the symptom recovery trajectory for each patient after inguinal hernia surgery is determined.

4. The intelligent follow-up system for postoperative rehabilitation management of inguinal hernia according to the integration of traditional Chinese and Western medicine, according to claim 3, characterized in that, The process of determining the comprehensive pathological differences in each patient after inguinal hernia surgery includes: Interpolation fitting was performed on the quantitative values ​​of the same symptom in all follow-up visits for each patient after inguinal hernia surgery to determine the time-series change curve of each symptom in each patient after inguinal hernia surgery. Global polynomial fitting was performed on the time-series change curves of the same symptom in all patients after inguinal hernia surgery in each cluster to determine the typical change curve of each symptom in each cluster. Record any symptom as the reference symptom. Based on the difference between the time-series change curve of the reference symptom presentation of each postoperative inguinal hernia patient in each cluster and the corresponding typical change curve, the degree of difference in the reference symptom presentation of each postoperative inguinal hernia patient is determined as a parameter. Based on the differences in the temporal change curves of the reference disease manifestations of different patients after inguinal hernia surgery in each cluster, as well as the differences in the comprehensive characteristics of the disease, the difference adjustment coefficient for the reference disease manifestations of each patient after inguinal hernia surgery was determined. The difference adjustment coefficient is used to correct the difference degree parameter to determine the comprehensive pathological difference parameter for each patient after inguinal hernia surgery.

5. The intelligent follow-up system for postoperative rehabilitation management of inguinal hernia according to the integration of traditional Chinese and Western medicine, characterized in that, The process of determining the degree of agreement between the comprehensive pathological manifestations and the distances between the basic physiological index vectors of different inguinal hernia patients after surgery includes: The first anastomosis value for each inguinal hernia patient is determined based on the distance between the basic physiological index vectors of different inguinal hernia patients in each cluster. Based on the differences in comprehensive pathological manifestations among patients after inguinal hernia surgery in each cluster, the second anastomosis value for each patient after inguinal hernia surgery was determined. The degree of agreement between the first and second anastomosis values ​​of each patient after inguinal hernia surgery is determined.

6. The intelligent follow-up system for postoperative rehabilitation management of inguinal hernia according to the integration of traditional Chinese and Western medicine, according to claim 4, characterized in that, The process of determining the difference adjustment coefficient for each postoperative inguinal hernia patient in terms of reference symptom presentation includes: In each cluster, any patient who has undergone surgery for inguinal hernia is designated as the target patient, and all other patients who have undergone surgery for inguinal hernia are designated as reference patients. Using the DTW algorithm, the DTW distance value between the time-series change curve of the reference symptom performance of the target patient and the time-series change curve of the reference symptom performance of each reference patient is obtained. Among the DTW distance values ​​between the time-series change curve of the reference symptom performance of the target patient and the time-series change curve of the reference symptom performance of all reference patients, all reference patients whose normalized DTW distance value is less than the preset similarity threshold are recorded as the main reference patients. Calculate the standard deviation of the comprehensive symptom characteristics of all primary reference patients to determine the reference dispersion; determine the reference difference value based on the absolute value of the difference between the mean of the comprehensive symptom characteristics of all primary reference patients and the comprehensive symptom characteristics of the target patient; and determine the difference adjustment coefficient of the target patient in the reference symptom characteristics by negatively normalizing the ratio between the reference difference value and the reference dispersion.

7. The intelligent follow-up system for postoperative rehabilitation management of inguinal hernia according to the integration of traditional Chinese and Western medicine, characterized in that, The process of using the difference adjustment coefficient to correct the difference degree parameter and determining the comprehensive pathological manifestation difference parameter for each inguinal hernia postoperative patient includes: The product of the difference adjustment coefficient and the difference degree parameter for each postoperative inguinal hernia patient in terms of the reference symptoms is recorded as the corrected difference parameter for each postoperative inguinal hernia patient in terms of the reference symptoms. The comprehensive pathological manifestation difference parameter for each patient after inguinal hernia surgery was determined based on the mean of the adjusted difference parameters across all disease manifestations.

8. The intelligent follow-up system for integrated traditional Chinese and Western medicine rehabilitation management after inguinal hernia surgery according to claim 5, characterized in that, The process of determining the first anastomosis value for each patient after inguinal hernia surgery includes: In each cluster, the average vector of the basic physiological indicators of all patients after inguinal hernia surgery is first obtained, and then the Euclidean distance between the average vector and the basic physiological indicator vector of each patient after inguinal hernia surgery is obtained. The inversely proportional normalized value of the Euclidean distance is recorded as the first concordance value of each patient after inguinal hernia surgery.

9. The intelligent follow-up system for postoperative rehabilitation management of inguinal hernia surgery using integrated traditional Chinese and Western medicine, as described in claim 5, is characterized in that... The process of determining the second anastomosis value for each patient after inguinal hernia surgery includes: Within each cluster, the comprehensive difference value between each inguinal hernia patient and any other inguinal hernia patient is determined based on the absolute value of the difference between the comprehensive pathological manifestation difference parameter of each inguinal hernia patient and any other inguinal hernia patient. The mean of the comprehensive difference values ​​of each inguinal hernia patient and all other inguinal hernia patients is then negatively correlated and normalized to determine the second anastomosis value for each inguinal hernia patient.

10. The intelligent follow-up system for postoperative rehabilitation management of inguinal hernia surgery using integrated traditional Chinese and Western medicine, as described in claim 5, is characterized in that... The process of determining the degree of agreement on the recovery trajectory of each inguinal hernia patient based on the magnitude of the first and second anastomosis values ​​includes: The average of the first and second anastomosis values ​​for each patient after inguinal hernia surgery is recorded as the degree of agreement of the patient's recovery trajectory after inguinal hernia surgery.

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