Traditional Chinese medicine data management method and system based on big data

Abstract

The invention relates to the technical field of data management, in particular to a traditional Chinese medicine data management method and system based on big data, and the method comprises the following steps: obtaining a traditional Chinese medicine management database through a traditional Chinese medicine data management system; establishing a data management optimization model according to the traditional Chinese medicine management database, and obtaining a traditional Chinese medicine time-feature information set by using the data management optimization model; a reference evaluation index of the traditional Chinese medicine data is set, an index evaluation result of the reference evaluation index is obtained based on the traditional Chinese medicine time-feature information set, and the management system adjusts and optimizes the traditional Chinese medicine time-feature information set according to the index evaluation result to obtain a traditional Chinese medicine information target set; and analyzing the traditional Chinese medicine use condition of the hospital based on the traditional Chinese medicine information target set so as to manage and monitor the traditional Chinese medicine use data and use condition of the hospital. According to the invention, the accuracy and efficiency of data management can be improved, the normalization and safety of traditional Chinese medicine administration are promoted, and the curative effect of traditional Chinese medicine in gynecological disease treatment is grasped.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a management method and system for traditional Chinese medicine data based on big data. Background Art

[0002] With the rapid development of information technology, the amount of data generated in the field of traditional Chinese medicine is also increasing. Among them, the clinical application data of traditional Chinese medicine related to gynecological diseases and gynecological treatments comes from various links, covering multiple aspects such as medicinal material planting, processing, compatibility, and efficacy feedback. In the field of gynecological diseases, due to the diversity of conditions and individual differences, the relevant data are highly complex and diverse.

[0003] Traditional Chinese medicine data management methods can perform simple data recording and sorting work in terms of basic data collection and storage. However, when dealing with the complexity and diversity challenges of current data management, the methods seem to be powerless. Traditional methods often find it difficult to explore the internal connections and laws between gynecological diseases and medication data. Existing Chinese medicine data management methods have solved the problems of Chinese medicine data collection and storage to a certain extent, but there are still obvious deficiencies in data mining and analysis. With the continuous increase of Chinese medicine information related to gynecological diseases, it is no longer possible to meet the development needs of the industry by simply staying at the basic data processing level. In order to more deeply reveal the internal laws and connections of Chinese medicine in the treatment of gynecological diseases, it is necessary to promote the progress and development of Chinese medicine data management methods, which can not only more effectively collect, store and manage Chinese medicine data, but also deeply explore the internal connections and laws between data, analyze the internal changes and trends of Chinese medicine data, thereby helping to achieve and grasp the efficacy and safety of Chinese medicine in the treatment of gynecological diseases, and provide more reliable data support for clinical decision-making. Summary of the invention

[0004] In view of the shortcomings of existing methods and the needs of practical applications, in order to deeply analyze and mine the internal connections, characteristic attributes and changes of hospital traditional Chinese medicine data, the in-depth application and development of traditional Chinese medicine data management system are promoted. On the one hand, the present invention provides a management method for traditional Chinese medicine data based on big data, which includes the following steps: obtaining a traditional Chinese medicine management database through the hospital's traditional Chinese medicine data management system; establishing a data management optimization model based on the traditional Chinese medicine management database, and using the data management optimization model to obtain a traditional Chinese medicine time-feature information set; setting a reference evaluation index for traditional Chinese medicine data, and obtaining an index evaluation result of the reference evaluation index based on the traditional Chinese medicine time-feature information set, and the traditional Chinese medicine data management system adjusts and optimizes the traditional Chinese medicine time-feature information set according to the index evaluation result to obtain a traditional Chinese medicine information target set; analyzing the hospital's traditional Chinese medicine medication situation based on the traditional Chinese medicine information target set to manage and monitor the hospital's traditional Chinese medicine medication data and usage. The present invention utilizes a data management optimization model to mine and optimize traditional Chinese medicine data, extracts valuable time-feature information sets, and provides a data basis for subsequent medication analysis. This can improve the efficiency and quality of traditional Chinese medicine data management, as well as the standardization and safety of traditional Chinese medicine use, and promote the rational use and optimal allocation of traditional Chinese medicine resources.

[0005] Optionally, the method of obtaining a Chinese medicine management database through the Chinese medicine data management system of the hospital includes: setting a data remote monitoring module, a data remote recording module and a data allocation monitoring module in the Chinese medicine data management system; obtaining the hospital's Chinese medicine dynamic management data through the data remote monitoring module; receiving and recording the Chinese medicine dynamic management data through the data remote recording module; performing status analysis on the Chinese medicine dynamic management data through the data allocation monitoring module, and obtaining a Chinese medicine management database based on the status analysis results. In the system of the present invention, multiple modules work together to ensure the integrity of Chinese medicine management data, and each step is the responsibility of the corresponding module, reducing the risk of data loss or omission.

[0006] Optionally, the establishment of a data management optimization model based on the traditional Chinese medicine management database includes: introducing a time series analysis method and a fuzzy mean clustering method; and establishing a data management optimization model in combination with the traditional Chinese medicine management database, the time series analysis method and the fuzzy mean clustering method. The present invention introduces a time series analysis method and a fuzzy mean clustering method, which can better cope with the complexity and diversity of traditional Chinese medicine data and help process and manage different types of traditional Chinese medicine data.

[0007] Optionally, the establishment of a data management optimization model by combining the Chinese medicine management database, the time series analysis method and the fuzzy mean clustering method includes: analyzing the Chinese medicine management database using the time series analysis method, and obtaining a time series-Chinese medicine data set of the Chinese medicine management database; extracting characteristic information of Chinese medicine data based on the Chinese medicine management database; and obtaining a time series characteristic data matrix by combining the time series-Chinese medicine data set and the characteristic information. The present invention can significantly improve the precision and accuracy of Chinese medicine data management, optimize Chinese medicine inventory management, and enhance the scientific nature of Chinese medicine medication decision-making, which helps hospitals better manage Chinese medicine data and improve the use effect and safety of Chinese medicine.

[0008] Optionally, the time series feature data matrix satisfies the following relationship:

[0009] in, represents the time series feature data matrix, Represents the first feature data in the first time series. Represents the second feature data in the first time series. Represents the third feature data in the first time series. represents the mth feature data in the first time series, Represents the first feature data in the second time series, Represents the second feature data in the second time series, represents the third feature data in the second time series, represents the mth feature data in the second time series, Represents the first feature data in the nth time series, Represents the second feature data in the nth time series, Represents the third feature data in the nth time series, Represents the mth feature data in the nth time series. The present invention shows the changing characteristics of Chinese medicine data in different time series, provides strong support for data analysis, mining, decision optimization and Chinese medicine research, helps hospitals better manage Chinese medicine data, and promotes the sustainable development of Chinese medicine management methods.

[0010] Optionally, the combination of the traditional Chinese medicine management database, the time series analysis method and the fuzzy mean clustering method to establish a data management optimization model includes: using the fuzzy mean clustering method to analyze the membership and characteristic distance of different time series features in the time series feature data matrix; and establishing a data management optimization model based on the membership, the characteristic distance and the fuzzy mean clustering method. The present invention is based on the fuzzy mean clustering method, and can more accurately describe the fuzzy relationship between data points by calculating the membership of each data point to different cluster centers.

[0011] Optionally, the establishing of a data management optimization model according to the traditional Chinese medicine management database, and obtaining the traditional Chinese medicine time-feature information set using the data management optimization model comprises: optimizing the time series feature data matrix through the data management optimization model to obtain the traditional Chinese medicine time-feature information set; The data management optimization model satisfies the following relationship:

[0012] in, Indicates the optimized time characteristic Chinese medicine information, represents the minimization objective function, represents n time series, Represents the mth feature data in n time series, Representing time series The membership degree with the mth feature, represents the fuzzy coefficient obtained based on the fuzzy mean clustering method, Represents the time series after optimization The present invention optimizes the time series feature data matrix through a data management optimization model, and can more accurately extract the time series information and feature information of traditional Chinese medicine data.

[0013] Optionally, the reference evaluation index for setting the traditional Chinese medicine data is obtained based on the traditional Chinese medicine time-feature information set. The traditional Chinese medicine data management system adjusts and optimizes the traditional Chinese medicine time-feature information set according to the index evaluation result, including: setting the reference evaluation index for the traditional Chinese medicine data based on the hospital's historical traditional Chinese medicine management data, the reference evaluation index including data transmission efficiency, data rationality and data security; the traditional Chinese medicine data management system adjusts and optimizes the traditional Chinese medicine time-feature information set according to the data transmission efficiency, the data rationality and the data security. The present invention sets reference evaluation indexes, and adjusts and optimizes the traditional Chinese medicine time-feature information set according to the indexes, which can improve the accuracy and reliability of traditional Chinese medicine data management and optimize the quality of the traditional Chinese medicine time-feature information set.

[0014] Optionally, the data transmission efficiency satisfies the following relationship:

[0015] in, represents the transmission rate of all TCM data in any time series, It represents the sum of the number of data actually collected for each data type during the monitoring period. It represents the sum of the number of data to be received for each data type during the monitoring period. As one of the important indicators for performance evaluation of the traditional Chinese medicine data management system, the data transmission efficiency of the present invention can be used to formulate and adjust the data management strategy to ensure timely and accurate data transmission.

[0016] In the second aspect, in order to be able to efficiently execute a management method for Chinese medicine data based on big data provided by the present invention, the present invention also provides a management system for Chinese medicine data based on big data, the above system includes a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the management method for Chinese medicine data based on big data as described in the first aspect of the present invention. The management system for Chinese medicine data based on big data of the present invention has a compact structure and stable performance, and can stably execute the management method for Chinese medicine data based on big data provided by the present invention, thereby improving the overall applicability and practical application ability of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of the management method of traditional Chinese medicine data based on big data of the present invention; Figure 2 It is a schematic diagram of the change trend of the relative importance index of different time series data sets in the management method of traditional Chinese medicine data based on big data of the present invention; Figure 3 This is a structural diagram of the management system for traditional Chinese medicine data based on big data of the present invention. DETAILED DESCRIPTION

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

[0019] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0020] See also Figure 1 In order to comprehensively and systematically optimize and upgrade the traditional Chinese medicine data management method, the present invention comprehensively uses big data technology, algorithms and models to analyze the inherent laws and changing trends of traditional Chinese medicine data. The present invention provides a traditional Chinese medicine data management method based on big data, and the above-mentioned traditional Chinese medicine data management method based on big data includes the following steps: S1. Obtain the Chinese medicine management database through the hospital's Chinese medicine data management system. The specific steps and implementation contents are as follows: In this embodiment, a data remote monitoring module, a data remote recording module and a data distribution monitoring module are set in the traditional Chinese medicine data management system. The steps of obtaining the traditional Chinese medicine management database are as follows: First, the hospital's dynamic management data of traditional Chinese medicine is obtained through the data remote monitoring module; Then, the dynamic management data of traditional Chinese medicine is received and recorded through the data remote recording module; Finally, the dynamic management data of traditional Chinese medicine is analyzed through the data allocation monitoring module, and the traditional Chinese medicine management database is obtained based on the status analysis results.

[0021] In an optional embodiment, the relevant process and specific contents of obtaining the traditional Chinese medicine management database are as follows: 1. System module settings In the hospital's traditional Chinese medicine data management system, the following core modules are set up to meet various data management needs. The data remote monitoring module is responsible for capturing the hospital's traditional Chinese medicine dynamic management data in real time to ensure the timeliness and accuracy of the data; the data remote recording module is responsible for receiving and properly recording the traditional Chinese medicine dynamic management data transmitted by the data remote monitoring module, providing a solid foundation for subsequent data analysis and utilization; the data distribution monitoring module performs status analysis on the traditional Chinese medicine dynamic management data, and builds a traditional Chinese medicine management database based on the analysis results, providing strong support for the management and clinical application of traditional Chinese medicine data.

[0022] 2. System Function Module Implementation In order to build a traditional Chinese medicine data management system with complete functions, convenient operation and rich information, the data remote monitoring module can realize the following functions.

[0023] Task management function: comprehensively manage various types of information of the hospital's traditional Chinese medicine management system, including but not limited to user management, project management and other aspects, to ensure the smooth promotion and operation of the traditional Chinese medicine data management system.

[0024] Data recording function: Through information technology, remote entry, modification, verification and tracking of TCM clinical trial data can be realized, thus improving the efficiency and accuracy of TCM data processing.

[0025] Remote query and monitoring function: Based on the Internet and authorized accounts, remote query and real-time monitoring of TCM clinical trials can be achieved to ensure the transparency and controllability of TCM data in the system.

[0026] Information sharing function: Build a multi-center clinical trial website in the system to promote the release and sharing of information on the use of traditional Chinese medicine and related data, and promote the effective development of traditional Chinese medicine data management technology.

[0027] In the data remote recording module, the following functions can be realized: Intelligent design of clinical trial CRF: realize the electronicization of CRF and ensure the information processing of clinical trial data.

[0028] Intelligent design of TCM syndrome scale: Establishing TCM syndrome scale can realize the quantitative processing of TCM syndromes, which is conducive to providing scientific basis for TCM clinical research.

[0029] Trial drug management: Receive and dynamically manage clinical trial drug data to ensure the standardization and safety of the distribution, recovery and destruction of traditional Chinese medicines.

[0030] Data synchronization and transmission: realize seamless connection of database system module information to ensure real-time synchronization and accurate transmission of traditional Chinese medicine data.

[0031] 3. Acquisition and Analysis of Traditional Chinese Medicine Management Database Through the data distribution monitoring module, the dynamic management data of traditional Chinese medicine is deeply analyzed to obtain the traditional Chinese medicine management database. The above database not only contains multi-dimensional traditional Chinese medicine data resources and related data, but also has the following characteristics: It can meet various needs of clinical trial data management in traditional Chinese medicine and form a standardized clinical research data management platform.

[0032] Provide a user interface and simple operation process to reduce users' learning cost and usage difficulty.

[0033] The Traditional Chinese Medicine Management Database contains various types of information on traditional Chinese medicine, such as drug sources, usage methods, efficacy evaluation, and traditional Chinese medicine inventory, providing all-round support for traditional Chinese medicine data management and clinical applications.

[0034] The traditional Chinese medicine management database obtained through the above process not only meets the various needs of traditional Chinese medicine clinical trial data management, but also provides relevant support for traditional Chinese medicine management and clinical application research, which helps to promote the effective development of traditional Chinese medicine research and drug data management methods.

[0035] Furthermore, the way in which the system acquires the traditional Chinese medicine management database in the embodiment is only an optional condition of the present invention. In one or some other embodiments, the way in which the traditional Chinese medicine database is acquired can be adjusted according to the actual operation of the hospital and the traditional Chinese medicine data management needs. This can ensure that the data management system is always synchronized with the operation of the hospital, meet the data management needs of the hospital at different stages, and at the same time improve the adaptability of the management system, improve data quality and method feasibility.

[0036] S2. Establish a data management optimization model based on the above-mentioned traditional Chinese medicine management database, and use the data management optimization model to obtain a set of traditional Chinese medicine time-feature information. The specific steps and implementation contents are as follows: In this embodiment, a fuzzy mean clustering method based on time series morphology is proposed to establish a data management optimization model, so that the data management optimization model has an efficient linear time complexity and can quickly process real-valued time series data. The fuzzy mean clustering method makes the model more accurate in identifying and analyzing the characteristics, similarities and differences of traditional Chinese medicine data. At the same time, the data management optimization model will be able to make full use of the advantages of time series analysis in processing time series data, as well as the powerful ability of fuzzy mean clustering in data classification and clustering.

[0037] First, the time series analysis method and fuzzy mean clustering method are introduced; it is necessary to combine the above-mentioned traditional Chinese medicine management database, time series analysis method and fuzzy mean clustering method to establish a data management optimization model.

[0038] Then, the traditional Chinese medicine management database is analyzed using the above time series analysis method, and a time series-traditional Chinese medicine data set of the traditional Chinese medicine management database is obtained; Based on the in-depth analysis of time series information and the relevant information in the pipeline Chinese medicine management database, the database is analyzed using a time series analysis method in the embodiment. Through this process, the time series data in the Chinese medicine management database can be extracted, and a Chinese medicine data set with time series characteristics is obtained, that is, the Chinese medicine management database time series-Chinese medicine data set in the embodiment is obtained. The above data set not only reflects the time series characteristics of Chinese medicine data, but also provides an analysis architecture foundation for subsequent information clustering analysis and data science management.

[0039] The embodiment further defines a time series-traditional Chinese medicine data set. In a given time series data, each time series has n independent time series in total. The n independent time series satisfy the following relationship:

[0040] in, Represents a time series-traditional Chinese medicine data set, Represents the time series data corresponding to the first time point, Represents the time series data corresponding to the second time point, Represents the time series data corresponding to the third time point, Represents the time series data corresponding to the nth time point.

[0041] Then, based on the above-mentioned traditional Chinese medicine management database, the characteristic information of the traditional Chinese medicine data is extracted; and the time series-traditional Chinese medicine data set and the characteristic information are combined to obtain the time series characteristic data matrix.

[0042] Time series data can be further represented as a matrix T with n rows and m columns, where m represents the number of features (or dimensions) of each time series, and n represents the total number of time series. In the above matrix, each column represents an independent time series, and each row represents the observed value of a feature in all time series.

[0043] In this embodiment, the time series feature data matrix is ​​a series of related observations arranged in chronological order. In the matrix, each time series is an observation sequence composed of m related features, and there are n such sequences in total. These sequences can represent the actual application of various traditional Chinese medicines, medical efficacy, drug performance indicators and other time series feature data.

[0044] The above time series feature data matrix satisfies the following relationship:

[0045] in, represents the time series feature data matrix, Represents the first feature data in the first time series. Represents the second feature data in the first time series. Represents the third feature data in the first time series. represents the mth feature data in the first time series, Represents the first feature data in the second time series, Represents the second feature data in the second time series, represents the third feature data in the second time series, represents the mth feature data in the second time series, Represents the first feature data in the nth time series, Represents the second feature data in the nth time series, Represents the third feature data in the nth time series, Represents the mth feature data in the nth time series.

[0046] In the management method of traditional Chinese medicine data based on big data proposed in the present invention, the time series feature data is stored in the form of a matrix, and each time series and its corresponding feature data are clearly presented, which is convenient for the subsequent analysis, understanding and management of the hospital's traditional Chinese medicine use. The above-mentioned structured data storage method makes data management and query simpler and more efficient, and can easily extract, modify or delete specific time series or feature data in the traditional Chinese medicine database.

[0047] Next, the fuzzy mean clustering method is used to analyze the membership and characteristic distance of different time series features in the time series feature data matrix; based on the above membership, characteristic distance and fuzzy mean clustering method, a data management optimization model is established.

[0048] In the embodiment, the time series feature data matrix is ​​clustered and analyzed by the fuzzy mean clustering method. Instead of simply dividing the data matrix into multiple mutually exclusive clusters, each time series is allowed to belong to multiple clusters at the same time with different memberships. The above membership is a continuous value between 0 and 1, which represents the degree of membership of the time series to the cluster. Based on the membership and the distance between the cluster centers, the optimal time feature family information in the system can be found, that is, the target set of traditional Chinese medicine information in the embodiment, so that the time series within the same cluster are more similar in characteristics, while the time series between different clusters are more different in characteristics.

[0049] In an optional embodiment, membership is analyzed. According to the data dynamic characteristics of the hospital's traditional Chinese medicine database and the actual needs of data management, an appropriate number of clusters C is selected; first, the membership matrix U needs to be initialized, and a membership matrix is ​​randomly generated, where n is the number of time series, and each element of the matrix Indicates The time series pair The membership of a cluster satisfies the following relationship: Furthermore, the initial cluster center can be randomly selected from C time series as the initial cluster center, or the initial cluster center can be calculated according to a certain strategy such as mean, median, etc.; the membership matrix and cluster center are continuously updated in an iterative manner until the stopping conditions are met, such as reaching the maximum number of iterations, the change in the objective function value is less than a certain threshold, etc.; the membership matrix is ​​updated, and a new membership matrix is ​​calculated based on the current cluster center and the objective function of fuzzy mean clustering, that is, based on the weighted sum of the distance between the membership and the cluster center, wherein the cluster center is updated, and a new cluster center can be calculated based on the new membership matrix, that is, the weighted average of all time series feature data, wherein the weighting coefficient is the membership.

[0050] The fuzzy mean clustering results can be used to perform pattern recognition on new time series and determine which cluster or combination of clusters it belongs to. The final membership matrix reveals the degree of membership of each time series to different clusters. By analyzing the membership matrix, we can understand the distribution of time series in the feature space and their relationship with different clusters.

[0051] In another alternative embodiment, feature distances are analyzed. The distance from the center of the mth feature It is a key indicator to measure the similarity of different time series. The smaller the distance, the closer the time series. The more similar it is to the feature center, the higher its membership degree to the feature center is likely to be.

[0052] The above membership is a value between 0 and 1, which reflects the degree of belonging of the time series to a certain feature center. When m increases, more feature centers are considered. If the distance to a feature center is significantly smaller than the distance to other feature centers, its membership will be closer to 1, indicating that it belongs to the feature center more clearly. On the contrary, if the distance between a time series and multiple feature centers is close, its membership among these feature centers will be more dispersed, showing stronger ambiguity.

[0053] When calculating the fuzzy degree of a time series belonging to a feature center, feature weight plays a vital role. Feature weight reflects the importance of different features in the clustering process. Multiplying the calculated feature distance by the feature weight of the cluster can adjust the contribution of feature distance in the membership calculation. Features with larger weights have a greater impact on the membership, so they can more effectively reflect the role of core features in the clustering process.

[0054] Based on this, not only the direct distance between the time series and the feature center can be considered, but also the importance information of the feature is incorporated, thereby improving the accuracy and robustness of the membership calculation.

[0055] In this embodiment, in order to better determine the time series The distance between the mth feature center is further combined with the composite distance and feature weight. In order to more comprehensively evaluate the similarity between the time series and the feature center, the composite distance between the features in the time series can be calculated. The composite distance can comprehensively consider the information of multiple features and provide a more comprehensive similarity measurement.

[0056] When calculating the composite distance, feature weights can be introduced to adjust the contribution of different features in the distance calculation. Features with larger weights will occupy a more important position in the distance calculation, thereby more accurately reflecting the similarity between the time series and the feature center.

[0057] In summary, the fuzzy degree of the time series belonging to the feature center can be expressed as follows: by calculating the composite distance between the time series and each feature center, and combining the feature weight to adjust the contribution of the distance in the membership calculation, the membership of the time series to each feature center is obtained. When considering feature centers with more time information, the membership of the time series will more clearly reflect the degree to which it belongs to a certain feature center; and when the feature weight is fully considered, the calculation result of the membership will be more accurate and robust.

[0058] Based on this, the distance between the optimized and adjusted time series and the feature center is obtained, and the following relationship is satisfied:

[0059] in, After optimization, , Indicates the number of time series dimensions and features, represents the composite distance function, represents the element of the n-th time series on the z-th feature, represents the element of feature m on the zth feature, Represents the feature weight corresponding to the zth feature.

[0060] Representing time series The distance from the center of the mth feature.

[0061] In the above process, the cluster center and the membership matrix will be continuously adjusted until a certain stopping condition is met, such as reaching the maximum number of iterations, the change of the membership matrix is ​​less than a certain threshold, etc., and finally a fuzzy cluster division can be obtained, which further reveals the complex distribution and relationship of the time series in the feature space.

[0062] In the embodiment, the fuzzy mean clustering method is combined with the analysis method of the concept of membership, allowing the time series to belong to multiple clusters at the same time, so as to more flexibly capture the complex relationship between the time series and extract the optimal time feature family information.

[0063] Based on the optimized time series The distance between the mth feature center can obtain the new optimal time feature family information, and satisfy the following relationship:

[0064] in, Indicates the optimized time characteristic Chinese medicine information, represents the minimization objective function, represents n time series, Represents the mth feature data in n time series, Representing time series The membership degree with the mth feature, represents the fuzzy coefficient obtained based on the fuzzy mean clustering method, Represents the time series after optimization The distance from the center of the mth feature.

[0065] The time series feature data matrix is ​​processed and optimized by applying the data management optimization model. This process aims to extract and analyze the key feature information of traditional Chinese medicine at different time points, so as to obtain a comprehensive and accurate set of time-feature information of traditional Chinese medicine, providing strong data support for the subsequent management and application of traditional Chinese medicine data.

[0066] Furthermore, in this embodiment, the optimized time-characteristic Chinese medicine information is verified and analyzed.

[0067] The verification and analysis process of the optimized time characteristic Chinese medicine information in the embodiment is as follows: In this example, six time series data sets are randomly selected as experimental objects for verification analysis. Based on the verification analysis results, a relative importance index change trend diagram of the time matrix is ​​drawn. For details, please refer to Figure 2 , where 1, 2, 3, 4, 5, and 6 represent six time series data sets, respectively, and RI represents the relative importance index in the fuzzy time matrix.

[0068] Figure 2The trend graph of the relative importance index (RI) of the fuzzy time matrix (FTM) changing with the matrix parameters is intuitively displayed. When the matrix parameter value range is between 1.1 and 5, it is found that the weight allocation strategy obviously tends to emphasize the importance of a single feature. As the matrix parameter value gradually increases, the above allocation strategy gradually becomes reasonable. At the same time, RI also shows a significant upward trend. The change shows that with the adjustment of the matrix parameter value, the ability of FTM in identifying key time features has been enhanced.

[0069] Subsequently, when the matrix parameter value continued to increase, the growth trend of RI gradually stabilized, which fully demonstrated the stability and robustness of FTM in identifying time characteristics. The above results not only verified the effectiveness of the optimized time characteristic Chinese medicine information, but also provided strong support for the subsequent Chinese medicine data management, research and application.

[0070] Furthermore, the specific steps and methods for obtaining the Chinese medicine information target set in the present embodiment are merely an optional condition of the present embodiment. In one or some other embodiments, the method for obtaining the Chinese medicine information target set may be adjusted according to the hospital's drug data management requirements and the data management system structure. Each hospital or drug management agency has its own unique drug data management requirements. In the present embodiment, the steps and methods for obtaining the Chinese medicine information target set are used as optional conditions, which can ensure that the embodiment can flexibly adapt to these different requirements and can ensure that the Chinese medicine information set matches the actual needs of the hospital.

[0071] S3. Set reference evaluation indicators for traditional Chinese medicine data, obtain the indicator evaluation results of the reference evaluation indicators based on the traditional Chinese medicine time-feature information set, and the traditional Chinese medicine data management system adjusts and optimizes the traditional Chinese medicine time-feature information set according to the indicator evaluation results to obtain the traditional Chinese medicine information target set. The specific steps and implementation contents are as follows: Reference evaluation indicators for traditional Chinese medicine data are set based on the hospital's historical traditional Chinese medicine management data. In the embodiment, the above-mentioned reference evaluation indicators mainly include data transmission efficiency, data rationality and data security; the traditional Chinese medicine data management system adjusts and optimizes the traditional Chinese medicine time-feature information set based on data transmission efficiency, data rationality and data security.

[0072] In the embodiment, reference evaluation indicators for Chinese medicine data are set mainly based on the hospital's historical Chinese medicine management data, which provides a clear direction for the optimization of the Chinese medicine data management system. The above indicators not only include key aspects such as data transmission, data rationality and data security, but also make the adjustment and optimization of the Chinese medicine time-feature information set more reliable through specific quantitative standards.

[0073] Analyze the reference evaluation indicators.

[0074] The data transmission efficiency can be calculated by the ratio of the number of actually received data to the number of receivable data, and then the efficiency of the hospital's traditional Chinese medicine data in the transmission process can be measured. The above data transmission efficiency satisfies the following relationship:

[0075] in, represents the transmission rate of all TCM data in any time series, It represents the sum of the number of data actually collected for each data type during the monitoring period. It indicates the sum of the number of data to be received for each data type during the monitoring period.

[0076] A higher data transmission efficiency means that the traditional Chinese medicine data information in the system can be accurately and timely transmitted to the management system, providing a basis for data analysis and management decisions for the management methods of traditional Chinese medicine data.

[0077] The data rationality index mainly focuses on the logic and consistency of traditional Chinese medicine data, ensuring that there are no errors or anomalies in the entry, processing and storage of traditional Chinese medicine data. By setting reasonable data verification rules and anomaly detection mechanisms, the unreasonable aspects of the data can be discovered and corrected in a timely manner, thereby improving the accuracy and credibility of the data.

[0078] Data security indicators need to emphasize the confidentiality, integrity and availability of traditional Chinese medicine data during storage, transmission and use. By adopting encryption technology, access control, data backup and recovery and other measures in the management methods of traditional Chinese medicine data, traditional Chinese medicine data can be effectively protected from risks such as unauthorized access, tampering and loss.

[0079] In an optional embodiment, the TCM time-feature information set is further adjusted and optimized based on the TCM data reference evaluation index.

[0080] Based on the above reference evaluation indicators, the TCM data management system makes the following adjustments and optimizations to the TCM time-feature information set: further improve the data transmission efficiency based on data transmission efficiency. Optimize the data transmission protocol and channel in the TCM data management system to reduce the delay and packet loss during the transmission of TCM data, and strengthen the transmission monitoring and alarm mechanism of TCM data to timely discover and solve the related problems in the transmission of TCM data in the system.

[0081] Strengthen the rationality verification process of TCM data in the system based on the rationality test results. Improve the data verification rules and anomaly detection mechanism in the TCM data management system to ensure the logic and consistency of TCM data, conduct regular quality inspections and evaluations on TCM data information, and promptly discover and correct the unreasonable aspects of the system data. On the other hand, strengthen data security, use advanced encryption technology and access control strategies in the TCM data management system to protect the confidentiality and integrity of TCM data, establish a complete TCM data backup and recovery mechanism, and ensure that TCM data can be restored in a timely manner when facing risks.

[0082] In summary, by setting reference evaluation indicators for TCM data based on the hospital's historical TCM management data and adjusting and optimizing the TCM time-feature information set according to relevant indicators, the efficiency and quality of TCM data management can be significantly improved, which will help to make a reasonable layout of TCM data management decisions and benefit the clinical application of TCM and the scientific development of digital medicine.

[0083] Furthermore, the method for adjusting and optimizing the traditional Chinese medicine information set in the present embodiment is only an optional condition of the present embodiment. In one or some other embodiments, the optimization adjustment method for the traditional Chinese medicine information set may be replaced according to the hospital drug data management requirements and the traditional Chinese medicine data management objectives. Different hospitals or data management agencies have different data management requirements and objectives. The method for adjusting and optimizing the traditional Chinese medicine database can ensure that the data management solution can meet the current diverse needs, thereby improving the operating efficiency and implementation effect of the traditional Chinese medicine data management method.

[0084] S4. Analyze the use of traditional Chinese medicine in the hospital based on the target set of traditional Chinese medicine information to manage and monitor the hospital's traditional Chinese medicine data and usage. The specific steps and implementation contents are as follows: Based on the TCM information target set, the hospital's TCM medication situation is analyzed to manage and monitor the hospital's TCM medication data and usage. The following are the specific steps and implementation contents of this stage: The reference Chinese medicine information set, the Chinese medicine historical management data set and the Chinese medicine usage specification information are compared with the Chinese medicine information target set to check whether the hospital's use of Chinese medicine complies with the specifications and whether there are any abnormal drug use situations.

[0085] A management method for traditional Chinese medicine data based on big data can also use statistical analysis, data mining and other methods to analyze traditional Chinese medicine usage data to reveal information such as existing trends in traditional Chinese medicine usage, commonly used traditional Chinese medicines, and drug compatibility.

[0086] Problem identification and report analysis are carried out based on the medication data and usage of the above-mentioned traditional Chinese medicines.

[0087] Based on the analysis results of TCM information, potential problems such as irrational use of TCM, drug abuse, and drug shortages are identified. At the same time, a detailed TCM use analysis report is generated, including but not limited to problem overview, cause analysis, recommended measures, etc., for reference by hospital management and relevant departments.

[0088] A management method for traditional Chinese medicine data based on big data also includes a monitoring and feedback mechanism.

[0089] The management method of traditional Chinese medicine data in this embodiment also incorporates big data technology and monitoring feedback mechanism. Based on this, a monitoring system for traditional Chinese medicine data and medication status can be constructed. The above system can track and analyze the dynamic changes of traditional Chinese medicine medication data in real time. If any data abnormality or deviation from expectations is found, the system will immediately send feedback information to the relevant departments and responsible persons so that necessary traditional Chinese medicine information adjustment measures can be taken quickly.

[0090] In practical applications, a management method for traditional Chinese medicine data based on big data covers the following key steps: Improvement of the target set of TCM information: In order to ensure the comprehensiveness and accuracy of TCM data, an accurate and effective TCM information database is constructed. The above information not only includes basic information such as the name, efficacy, usage and dosage of TCM, but also covers key contents such as TCM compatibility, contraindications and measurement, laying a solid foundation for subsequent TCM data management and analysis.

[0091] Selection of TCM data analysis tools: Based on the actual situation of the hospital and the needs of drug data management, efficient data analysis tools and methods such as SPSS, SAS, and Python can be selected to further improve the accuracy of TCM information analysis results and the smoothness of related system operation.

[0092] Establishment of a multi-department collaboration mechanism in the hospital: In order to promote the comprehensive collection, in-depth analysis and continuous improvement of TCM medication data, strengthen communication and collaboration among multiple departments such as the hospital pharmacy, TCM clinical department, and TCM information department, and form a mutual collaboration and coordination working mechanism.

[0093] The above measures and specific implementation plans will help hospitals to fully and systematically understand, monitor and manage the use of traditional Chinese medicine, timely discover and correct problems in the use of traditional Chinese medicine, and thus ensure the rationality, safety and effectiveness of traditional Chinese medicine. At the same time, it provides strong technical support for the scientific management and real-time monitoring of traditional Chinese medicine data in hospitals, and promotes the overall improvement of the management level and actual application effect of traditional Chinese medicine in hospitals.

[0094] See also Figure 3In an optional embodiment, in order to efficiently execute the management method of traditional Chinese medicine data based on big data provided by the present invention, the present invention also provides a management system for traditional Chinese medicine data based on big data, the management system for traditional Chinese medicine data based on big data includes a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and execute the specific steps of the relevant embodiments of the management method for traditional Chinese medicine data based on big data provided by the present invention. The management system for traditional Chinese medicine data based on big data of the present invention has a complete structure, is objective and stable, and can efficiently execute the management method for traditional Chinese medicine data based on big data of the present invention, thereby improving the overall applicability and practical application ability of the present invention.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for managing traditional Chinese medicine data based on big data, characterized in that: The steps include: Obtain the Chinese medicine management database through the hospital's Chinese medicine data management system; Establishing a data management optimization model according to the traditional Chinese medicine management database, and using the data management optimization model to obtain a traditional Chinese medicine time-feature information set; Setting a reference evaluation index for traditional Chinese medicine data, obtaining an index evaluation result of the reference evaluation index based on the traditional Chinese medicine time-feature information set, and adjusting and optimizing the traditional Chinese medicine time-feature information set according to the index evaluation result to obtain a traditional Chinese medicine information target set; The use of traditional Chinese medicine in the hospital is analyzed based on the traditional Chinese medicine information target set to manage and monitor the hospital's traditional Chinese medicine data and usage.

2. The method for managing traditional Chinese medicine data based on big data according to claim 1, characterized in that: The method of obtaining the traditional Chinese medicine management database through the hospital's traditional Chinese medicine data management system includes: A data remote monitoring module, a data remote recording module and a data distribution monitoring module are set in the traditional Chinese medicine data management system; Obtaining the hospital's traditional Chinese medicine dynamic management data through the data remote monitoring module; Receive and record the dynamic management data of traditional Chinese medicine through the remote data recording module; The data distribution monitoring module is used to perform status analysis on the dynamic management data of traditional Chinese medicine, and a traditional Chinese medicine management database is obtained based on the status analysis results.

3. The method for managing traditional Chinese medicine data based on big data according to claim 1, characterized in that: The establishing of a data management optimization model according to the traditional Chinese medicine management database comprises: Introducing time series analysis methods and fuzzy mean clustering methods; A data management optimization model is established by combining the traditional Chinese medicine management database, the time series analysis method and the fuzzy mean clustering method.

4. The method for managing traditional Chinese medicine data based on big data according to claim 3, characterized in that: The method of establishing a data management optimization model by combining the traditional Chinese medicine management database, the time series analysis method and the fuzzy mean clustering method comprises: Analyzing the traditional Chinese medicine management database using the time series analysis method, and obtaining a time series-traditional Chinese medicine data set of the traditional Chinese medicine management database; Extracting characteristic information of traditional Chinese medicine data based on the traditional Chinese medicine management database; The time series-traditional Chinese medicine data set and the characteristic information are combined to obtain a time series characteristic data matrix.

5. The method for managing traditional Chinese medicine data based on big data according to claim 4, characterized in that: The time series feature data matrix satisfies the following relationship: ， in, represents the time series feature data matrix, Represents the first feature data in the first time series. Represents the second feature data in the first time series. Represents the third feature data in the first time series. represents the mth feature data in the first time series, Represents the first feature data in the second time series, Represents the second feature data in the second time series, represents the third feature data in the second time series, represents the mth feature data in the second time series, Represents the first feature data in the nth time series, Represents the second feature data in the nth time series, Represents the third feature data in the nth time series, Represents the mth feature data in the nth time series.

6. The method for managing traditional Chinese medicine data based on big data according to claim 4, characterized in that: The method of establishing a data management optimization model by combining the traditional Chinese medicine management database, the time series analysis method and the fuzzy mean clustering method comprises: The fuzzy mean clustering method is used to analyze the membership and feature distance of different time series features in the time series feature data matrix; A data management optimization model is established based on the membership degree, the characteristic distance and the fuzzy mean clustering method.

7. The method for managing traditional Chinese medicine data based on big data according to claim 6, characterized in that: The establishing of a data management optimization model according to the traditional Chinese medicine management database and obtaining a traditional Chinese medicine time-feature information set using the data management optimization model comprises: The time series characteristic data matrix is ​​optimized by the data management optimization model to obtain a set of time-characteristic information of traditional Chinese medicine; The data management optimization model satisfies the following relationship: ， in, Indicates the optimized time characteristic Chinese medicine information, represents the minimization objective function, represents n time series, Represents the mth feature data in n time series, Representing time series The membership degree with the mth feature, represents the fuzzy coefficient obtained based on the fuzzy mean clustering method, Represents the time series after optimization The distance from the center of the mth feature.

8. The method for managing traditional Chinese medicine data based on big data according to claim 1, characterized in that: The setting of reference evaluation indicators for traditional Chinese medicine data, obtaining an indicator evaluation result of the reference evaluation indicator based on the traditional Chinese medicine time-feature information set, and the traditional Chinese medicine data management system adjusting and optimizing the traditional Chinese medicine time-feature information set according to the indicator evaluation result include: Setting reference evaluation indicators for traditional Chinese medicine data based on the hospital's historical traditional Chinese medicine management data, the reference evaluation indicators including data transmission efficiency, data rationality and data security; The traditional Chinese medicine data management system adjusts and optimizes the traditional Chinese medicine time-feature information set based on the data transmission efficiency, the data rationality and the data security.

9. The method for managing traditional Chinese medicine data based on big data according to claim 8, characterized in that: The data transmission efficiency satisfies the following relationship: ， in, represents the transmission rate of all TCM data in any time series, It represents the sum of the number of data actually collected for each data type during the monitoring period. It indicates the sum of the number of data to be received for each data type during the monitoring period.

10. A management system for traditional Chinese medicine data based on big data, characterized in that: The system includes a processor, an input device, an output device and a memory, wherein the processor, input device, output device and memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the management method of traditional Chinese medicine data based on big data as described in any one of claims 1-9.

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