A method and system for managing traditional Chinese medicine data based on big data

Abstract

The present application relates to the technical field of data management, in particular to a traditional Chinese medicine data management method and system based on big data, which 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; setting reference evaluation indexes of traditional Chinese medicine data, obtaining index evaluation results of the reference evaluation indexes 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 results to obtain a traditional Chinese medicine information target set; analyzing the traditional Chinese medicine medication of a hospital based on the traditional Chinese medicine information target set to manage and monitor the traditional Chinese medicine medication data and use of the hospital. The present application can improve the accuracy and efficiency of data management, promote the standardization and safety of traditional Chinese medicine medication, and grasp the curative effect of traditional Chinese medicine in the treatment of gynecological diseases.

Description

TECHNICAL FIELD

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

[0002] With the rapid development of information technology, the amount of data generated in the field of traditional Chinese medicine is also growing. Among them, the clinical application data of traditional Chinese medicine for gynecological diseases and gynecological treatment come from various aspects, covering medicine planting, processing, compatibility, efficacy feedback and other aspects. In the field of gynecological diseases, due to the diversity of disease conditions and large individual differences, the related data presents high complexity and diversity.

[0003] Traditional traditional Chinese medicine data management methods can perform simple data recording and sorting work in basic data collection and storage. However, when dealing with the complexity and diversity of current data management, the method is not up to the task. Traditional methods often have difficulty in mining the internal relationship and regularity between gynecological diseases and medication data. The existing traditional Chinese medicine data management method solves the problem of traditional 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 gynecological disease related traditional Chinese medicine information, only staying at the basic processing level of data has been unable to meet the development needs of the industry. In order to more deeply reveal the internal rules and relationships of traditional Chinese medicine in the treatment of gynecological diseases, it is necessary to promote the progress and development of traditional Chinese medicine data management method, not only can more effectively collect, store and manage traditional Chinese medicine data, but also can deeply mine the internal relationship and regularity between data, analyze the internal change and trend of traditional Chinese medicine data, so as to help realize and grasp the efficacy and safety of traditional Chinese medicine in the treatment of gynecological diseases, and provide more reliable data support for clinical decision-making. SUMMARY

[0004] In view of the deficiencies of the existing methods and the needs of practical applications, in order to deeply analyze and mine the internal relations, characteristic attributes and change conditions of traditional Chinese medicine data in hospitals, and promote the in-depth application and development of traditional Chinese medicine data management system, the present application provides a traditional Chinese medicine data management method based on big data, which comprises the following steps: obtaining a traditional Chinese medicine management database through a traditional Chinese medicine data management system of a hospital; 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; setting a reference evaluation index of 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 by the traditional Chinese medicine data management system, to obtain a traditional Chinese medicine information target set; analyzing the traditional Chinese medicine use condition of the hospital based on the traditional Chinese medicine information target set, to manage and monitor the traditional Chinese medicine use data and use condition of the hospital. The present application uses a data management optimization model to mine and optimize traditional Chinese medicine data, extracts a valuable time-feature information set, provides a data basis for subsequent medication analysis, can improve the efficiency and quality of traditional Chinese medicine data management, can also improve the standardization and safety of traditional Chinese medicine use, and promotes the rational use and optimal allocation of traditional Chinese medicine resources.

[0005] Optionally, the obtaining of the traditional Chinese medicine management database through the traditional Chinese medicine data management system of the hospital comprises: setting a data remote monitoring module, a data remote recording module and a data distribution monitoring module in the traditional Chinese medicine data management system; obtaining traditional Chinese medicine dynamic management data of the hospital through the data remote monitoring module; receiving and recording the traditional Chinese medicine dynamic management data through the data remote recording module; and performing state analysis on the traditional Chinese medicine dynamic management data through the data distribution monitoring module, to obtain a traditional Chinese medicine management database based on the state analysis result. The multiple modules in the system work cooperatively, can ensure the integrity of the traditional Chinese medicine management data, each step is responsible by the corresponding module, and the risk of data loss or omission is reduced.

[0006] Optionally, the establishing of the data management optimization model according to the traditional Chinese medicine management database comprises: introducing a time series analysis method and a fuzzy mean clustering method; and combining the traditional Chinese medicine management database, the time series analysis method and the fuzzy mean clustering method to establish the data management optimization model. The present application introduces the time series analysis method and the fuzzy mean clustering method, can better cope with the complexity and diversity of traditional Chinese medicine data, and is helpful to process and manage different kinds of traditional Chinese medicine data.

[0007] Optionally, the 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, comprising: analyzing the traditional Chinese medicine management database by using the time series analysis method, and obtaining a time series-traditional Chinese medicine data set of the traditional Chinese medicine management database; extracting feature information of traditional Chinese medicine data based on the traditional Chinese medicine management database; and obtaining a time series feature data matrix by combining the time series-traditional Chinese medicine data set and the feature information. The present application can significantly improve the accuracy and accuracy of traditional Chinese medicine data management, optimize traditional Chinese medicine inventory management, and improve the scientific nature of traditional Chinese medicine decision-making, which helps hospitals better manage traditional Chinese medicine data and improve the use effect and safety of traditional Chinese medicine.

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

[0009]

[0010] wherein, denotes the time series feature data matrix, denotes the first feature data in the first time series, denotes the second feature data in the first time series, denotes the third feature data in the first time series, denotes the mth feature data in the first time series, denotes the first feature data in the second time series, denotes the second feature data in the second time series, denotes the third feature data in the second time series, denotes the mth feature data in the second time series, denotes the first feature data in the nth time series, denotes the second feature data in the nth time series, denotes the third feature data in the nth time series, denotes the mth feature data in the nth time series. The present application shows the change characteristics of traditional Chinese medicine data in different time series, which provides strong support for data analysis, mining, decision optimization and traditional Chinese medicine research, and helps hospitals better manage traditional Chinese medicine data and promote the sustainable development of traditional Chinese medicine management methods.

[0011] Optionally, the 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, comprising: analyzing the membership degree and feature distance of different time series features in the time series feature data matrix by using the fuzzy mean clustering method; and establishing the data management optimization model based on the membership degree, the feature distance and the fuzzy mean clustering method. The fuzzy mean clustering method can more accurately describe the fuzzy relationship between data points by calculating the membership degree of each data point to different clustering centers.

[0012] Optionally, the data management optimization model is established according to the traditional Chinese medicine management database, and the traditional Chinese medicine time-feature information set is obtained by using the data management optimization model, comprising: optimizing the time series feature data matrix by using the data management optimization model to obtain the traditional Chinese medicine time-feature information set.

[0013] The data management optimization model satisfies the following relationship:

[0014]

[0015] Wherein, represents the optimized time feature traditional Chinese medicine information, represents the minimized objective function, represents n time series, represents the mth feature data in the n time series, represents the time series and the membership degree of the mth feature, represents the fuzzy coefficient obtained based on the fuzzy mean clustering method, represents the distance between the optimized time series and the mth feature center. The data management optimization model can more accurately extract the time series information and feature information of traditional Chinese medicine data by optimizing the time series feature data matrix.

[0016] Optionally, the reference evaluation index of the traditional Chinese medicine data is set based on the index evaluation result of the reference evaluation index obtained 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, comprising: setting the reference evaluation index of the traditional Chinese medicine data based on the historical traditional Chinese medicine management data of the hospital, the reference evaluation index comprising data transmission efficiency, data rationality and data security; and 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 reference evaluation index is set in the application, and the traditional Chinese medicine time-feature information set is adjusted and optimized according to the index, so that the accuracy and reliability of traditional Chinese medicine data management can be improved, and the quality of the traditional Chinese medicine time-feature information set can be optimized.

[0017] Optionally, the data transmission efficiency satisfies the following relationship:

[0018]

[0019] wherein, represents the transmission rate of all traditional Chinese medicine data in any time sequence, represents the sum of the actual received data quantity of each data type in the monitoring period, represents the sum of the expected received data quantity of each data type in the monitoring period. The data transmission efficiency of the application can be used as one of the important indexes for evaluating the performance of the traditional Chinese medicine data management system, and the data management strategy can be formulated and adjusted according to the efficiency to ensure the timely and accurate transmission of data.

[0020] In the second aspect, in order to efficiently execute the management method of traditional Chinese medicine data based on big data provided by the application, the application further provides a management system of traditional Chinese medicine data based on big data. The system comprises a processor, an input device, an output device and a memory, and the processor, the input device, the output device and the memory are connected to each other. The memory is used to store a computer program, the computer program comprises 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 the first aspect of the application. The management system of traditional Chinese medicine data based on big data has a compact structure and stable performance, and can stably execute the management method of traditional Chinese medicine data based on big data provided by the application, thereby improving the overall applicability and practical application ability of the application. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 The flow chart of the management method of traditional Chinese medicine data based on big data of the application;

[0022] Figure 2The figure shows 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 application;

[0023] Figure 3 The figure shows the structure of the management system of traditional Chinese medicine data based on big data of the application. DETAILED DESCRIPTION

[0024] The specific embodiments of the application will be described in detail below, and it should be noted that the embodiments described herein are only used for illustration and do not limit the application. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the application. However, it is obvious to those skilled in the art that the specific details need not be used to practice the application. In other instances, well-known circuits, software or methods have not been specifically described in order to avoid obscuring the application.

[0025] Throughout the specification, references to "one embodiment", "an embodiment", "one example", or "an example" mean that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment of the application. Therefore, the appearance of the phrases "in one embodiment", "in an embodiment", "one example" or "an example" at various places throughout the specification is not necessarily all referring to the same embodiment or example. In addition, specific features, structures, or characteristics can be combined in any suitable combination and / or subcombination in one or more embodiments or examples. In addition, those skilled in the art should understand that the diagrams provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0026] Please refer to Figure 1 In order to comprehensively and systematically optimize and upgrade the traditional Chinese medicine data management method, the application comprehensively uses big data technology, algorithm and model to analyze the internal laws and change trends of traditional Chinese medicine data. The application provides a management method for traditional Chinese medicine data based on big data, which comprises the following steps:

[0027] S1, obtaining a traditional Chinese medicine management database through a hospital traditional Chinese medicine data management system, and the specific steps and implementation contents are as follows:

[0028] 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, and the steps of obtaining the traditional Chinese medicine management database are as follows:

[0029] Firstly, the traditional Chinese medicine dynamic management data of the hospital is obtained through the data remote monitoring module;

[0030] Then, the traditional Chinese medicine dynamic management data is received and recorded through the data remote recording module;

[0031] Finally, the traditional Chinese medicine dynamic management data is analyzed by the data distribution monitoring module, and the traditional Chinese medicine management database is obtained based on the analysis results.

[0032] In an optional embodiment, the related process and specific content of obtaining the traditional Chinese medicine management database are as follows:

[0033] I. System module setting

[0034] In the traditional Chinese medicine data management system of the hospital, the following core modules are set to meet the various needs of data management. The data remote monitoring module is responsible for capturing the traditional Chinese medicine dynamic management data of the hospital in real time, ensuring 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 analyzes the traditional Chinese medicine dynamic management data, and constructs the traditional Chinese medicine management database based on the analysis results, providing strong support for the management and clinical application of traditional Chinese medicine data.

[0035] II. Implementation of system function module

[0036] In order to build a traditional Chinese medicine data management system with perfect functions, convenient operation and rich information, the data remote monitoring module can realize the following functions.

[0037] Task management function: comprehensively manage various information of the hospital traditional Chinese medicine management system, including but not limited to user management, project management and other aspects, to ensure the smooth progress and operation of the traditional Chinese medicine data management system.

[0038] Data recording function: through information means, realize the remote input, modification, verification and tracing of traditional Chinese medicine clinical trial data, improve the efficiency and accuracy of traditional Chinese medicine data processing.

[0039] Remote query and monitoring function: based on the Internet and authorized accounts, realize the remote query and real-time monitoring of traditional Chinese medicine clinical trials, ensure the transparency and controllability of the system traditional Chinese medicine data.

[0040] Information sharing function: build a multi-center clinical trial website in the system, promote the publication and information sharing of traditional Chinese medicine use information and related data, and effectively promote the development of traditional Chinese medicine data management technology.

[0041] In the data remote recording module, the following functions can be realized:

[0042] Clinical trial CRF intelligent design: realize the electrification of CRF, and ensure the information processing of clinical trial data.

[0043] Intelligent design of TCM syndrome scale: Establishing a TCM syndrome scale can realize the quantitative processing of TCM syndromes, which is conducive to providing a scientific basis for TCM clinical research.

[0044] 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.

[0045] 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.

[0046] 3. Acquisition and Analysis of Traditional Chinese Medicine Management Database

[0047] Through the data distribution monitoring module, we conduct in-depth analysis of the dynamic management data of traditional Chinese medicine, and then obtain a traditional Chinese medicine management database. This database not only contains multi-dimensional traditional Chinese medicine data resources and related data, but also has the following characteristics:

[0048] It can meet various needs of clinical trial data management of traditional Chinese medicine and form a standardized clinical research data management platform.

[0049] Provides a user interface and simple operation process to reduce users' learning costs and usage difficulty.

[0050] 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.

[0051] Through the above process, a traditional Chinese medicine management database was obtained, which 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, and helps to promote the effective development of traditional Chinese medicine research and drug data management methods.

[0052] 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, enhance data quality and method feasibility.

[0053] 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:

[0054] In the embodiment, a fuzzy mean clustering method based on time series pattern is proposed to establish a data management optimization model, so that the data management optimization model has high 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 can fully utilize the advantages of time series analysis in processing time series data and the powerful ability of fuzzy mean clustering in data classification and clustering.

[0055] Firstly, the time series analysis method and the fuzzy mean clustering method are introduced; the data management optimization model needs to be established by combining the above traditional Chinese medicine management database, the time series analysis method and the fuzzy mean clustering method.

[0056] Then, the traditional Chinese medicine management database is analyzed by using the above time series analysis method, and the time series-traditional Chinese medicine data set of the traditional Chinese medicine management database is obtained.

[0057] Based on the in-depth analysis of the time sequence information and the related information in the pipeline traditional Chinese medicine management database, the time series analysis method is used to analyze the database in the embodiment. Through this process, the time series data in the traditional Chinese medicine management database can be extracted, and the traditional Chinese medicine data set with time sequence characteristics is obtained, i.e. the time series-traditional Chinese medicine data set of the traditional Chinese medicine management database in the embodiment. The above data set not only reflects the time sequence characteristics of traditional Chinese medicine data, but also provides an analysis architecture foundation for subsequent information clustering analysis and data science management.

[0058] The time series-traditional Chinese medicine data set is further defined in the embodiment. In a given time series data, each time series has n independent time series, and the n independent time series satisfy the following relationship:

[0059]

[0060] Wherein, represents the 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 n-th time point.

[0061] Then, the characteristic information of traditional Chinese medicine data is extracted based on the above traditional Chinese medicine management database; and the time series characteristic data matrix is obtained by combining the time series-traditional Chinese medicine data set and the characteristic information.

[0062] The time series data can be further represented as a matrix T of n rows and m columns, where m represents the number of characteristics (or dimensions) of each time series, and n represents the total number of time series, each column of the above matrix represents an independent time series, and each row represents the observation value of a characteristic in all time series.

[0063] In the embodiment, the time series characteristic data matrix is a series of related observation values arranged in chronological order. In the matrix, each time series is a sequence of observation values composed of m related characteristics, and there are n such sequences in total, which can represent various time series characteristic data of actual application of traditional Chinese medicine, medical use efficacy, and drug performance indicators.

[0064] The above time series characteristic data matrix satisfies the following relationship:

[0065]

[0066] wherein, represents the time series characteristic data matrix, represents the first characteristic data in the first time series, represents the second characteristic data in the first time series, represents the third characteristic data in the first time series, represents the mth characteristic data in the first time series, represents the first characteristic data in the second time series, represents the second characteristic data in the second time series, represents the third characteristic data in the second time series, represents the mth characteristic data in the second time series, represents the first characteristic data in the n th time series, represents the second characteristic data in the n th time series, represents the third characteristic data in the n th time series, represents the mth characteristic data in the n th time series.

[0067] In the management method of traditional Chinese medicine data based on big data provided by the application, the time series characteristic data is stored in the form of a matrix, each time series and its corresponding characteristic data is clearly presented, which is convenient for subsequent analysis, understanding and management of the use of traditional Chinese medicine in hospitals. The above structured data storage method makes the management and query of data more simple and efficient, and the specific time series or characteristic data in the traditional Chinese medicine database can be conveniently extracted, modified or deleted.

[0068] Then, the membership and feature distance of different time series features in the time series feature data matrix are analyzed by using the fuzzy mean clustering method; and a data management optimization model is established based on the above membership, feature distance and fuzzy mean clustering method.

[0069] In the embodiment, the time series feature data matrix is analyzed by using 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 different membership degrees. The membership degree is a continuous value between 0 and 1, representing the membership degree of the time series to the cluster. Based on the distance between the membership degree and the cluster center, the optimal time feature family information in the system, i.e., the traditional Chinese medicine information target set in the embodiment, can be found, so that the time series in the same cluster are more similar in features, and the time series in different clusters are more different in features.

[0070] In an optional embodiment, the membership is analyzed. According to the dynamic characteristics of the hospital traditional Chinese medicine database and the actual needs of data management, a suitable 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 represents the membership of the i-th time series to the j-th cluster, and satisfies the following relationship: Further, the initial cluster centers can be randomly selected as C time series, or calculated according to a certain strategy such as mean, median, etc.; the membership matrix and the cluster centers are updated iteratively until the stopping condition is met, such as reaching the maximum number of iterations, the change of the objective function value being less than a certain threshold, etc.; the membership matrix is updated, and the new membership matrix is calculated according to the current cluster centers and the objective function of the fuzzy mean clustering, i.e., the weighted sum based on the distance between the membership and the cluster center; the cluster centers are updated, and the new cluster centers are calculated according to the new membership matrix, i.e., the weighted average of all time series feature data, where the weighting coefficient is the membership.

[0071] The fuzzy mean clustering result can be used for pattern recognition of new time series to determine which cluster or combination of clusters it belongs to. The final membership matrix reveals the membership degree of each time series to different clusters. By analyzing the membership matrix, the distribution of time series in the feature space and their relationship with different clusters can be understood.

[0072] In another optional embodiment, the feature distance is analyzed. The distance between the i-th time series and the m-th feature center is a key indicator for measuring the similarity of different time series. The smaller the distance, the more similar the time series.​​​​ The more similar the feature center is, the higher the membership of the time series to the feature center can be.

[0073] The membership is a value between 0 and 1, which reflects the degree of the time series belonging to a certain feature center. When m increases, more feature centers are considered, and if the time series If the distance of the time series to a certain 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 definitely. Conversely, if the time series is similar to multiple feature centers, its membership in these feature centers will be more scattered, showing stronger fuzziness.

[0074] In calculating the fuzzy degree of the time series belonging to the feature center, feature weights play a crucial role. Feature weights reflect the importance of different features in the clustering process. By multiplying the calculated feature distance with the feature weight of the cluster, the contribution of the feature distance in the membership calculation can be adjusted. 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.

[0075] 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 integrated, thereby improving the accuracy and robustness of the membership calculation.

[0076] In this embodiment, in order to better determine the distance between the time series and the mth feature center, a method combining composite distance and feature weight is further adopted. In order to more comprehensively evaluate the similarity between the time series and the feature center, the composite distance between each feature in the time series can be calculated. The above composite distance can comprehensively consider the information of multiple features, providing a more comprehensive similarity measure.

[0077] In calculating the composite distance, feature weights can be introduced to adjust the contribution of different features in distance calculation. Features with larger weights will play a more important role in distance calculation, thereby more accurately reflecting the similarity between the time series and the feature center.

[0078] 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 more time information of the feature center, the membership of the time series will more clearly reflect its degree of belonging to a certain feature center. When the feature weight is fully considered, the calculation result of the membership will be more accurate and robust.

[0079] Based on this, the distance between the time series after optimization adjustment and the feature center is obtained, and satisfies the following relationship:

[0080]

[0081] wherein, denotes the optimized , denotes the number of time series dimensions and features, denotes a composite distance function, denotes the element of the n time series on the z feature, denotes the element of the m feature on the z feature, denotes the feature weight corresponding to the z pair.

[0082] denotes the distance between the time series and the mth feature center.

[0083] In the above process, the cluster center and membership matrix are continuously adjusted until a certain stopping condition is met, such as reaching the maximum number of iterations, the change in membership matrix being less than a certain threshold, etc. Finally, a fuzzy cluster partition can be obtained, further revealing the complex distribution and relationship of time series in feature space.

[0084] In the embodiment, the fuzzy mean clustering method combined with the analysis method of membership concept is adopted, which allows the time series to belong to multiple clusters at the same time, thereby more flexibly capturing the complex relationship between time series and extracting the optimal time feature family information.

[0085] Based on the distance between the time series and the mth feature center after optimization, the new optimal time feature family information can be obtained, and satisfies the following relationship:

[0086]

[0087] wherein, denotes the optimized time feature information, denotes the minimized objective function, denotes the n time series, denotes the mth feature data in the n time series, denotes the distance between the time series and the mth feature, denotes the fuzzy coefficient obtained based on the fuzzy mean clustering method, denotes the distance between the time series and the mth feature center after optimization.

[0088] By applying the data management optimization model to process and optimize the time series characteristic data matrix, this process aims to extract and analyze the key feature information of traditional Chinese medicine at different time points, thereby obtaining a comprehensive and accurate traditional Chinese medicine time-feature information set, providing strong data support for subsequent traditional Chinese medicine data management and application.

[0089] Further, in this embodiment, the optimized time-feature traditional Chinese medicine information is verified and analyzed.

[0090] The verification and analysis process of the optimized time-feature traditional Chinese medicine information in the embodiment is as follows:

[0091] In this embodiment, six time series data sets are randomly selected as experimental objects for verification and analysis, and based on the verification and analysis results, a relative importance index trend graph of the time matrix is drawn, please refer to Figure 2 , wherein 1, 2, 3, 4, 5, and 6 represent the six time series data sets, and RI represents the relative importance index in the fuzzy time matrix.

[0092] Figure 2 The trend graph intuitively shows that the relative importance index (RI) of the fuzzy time matrix (FTM) changes with the matrix parameter, when the value range of the matrix parameter is between 1.1 and 5, it is found that the allocation strategy of the weight value obviously tends to emphasize the importance of a single feature, and as the matrix parameter value gradually increases, the above allocation strategy gradually tends to be reasonable, at the same time, RI also presents a significant upward trend, and the change indicates that as the matrix parameter value is adjusted, the ability of FTM in identifying key time features is enhanced.

[0093] Subsequently, when the matrix parameter value continues to increase, the growth trend of RI gradually tends to be stable, which fully demonstrates the robustness and robustness of FTM in identifying time features, and the above results not only verify the effectiveness of the optimized time-feature traditional Chinese medicine information, but also provide strong support for subsequent traditional Chinese medicine data management, research and application.

[0094] Further, the specific steps and methods of obtaining the target set of traditional Chinese medicine information in this embodiment are only optional conditions for this embodiment, in other one or some embodiments, the method of obtaining the target set of traditional Chinese medicine information can be adjusted according to the hospital drug data management needs and the structure of the data management system. Each hospital or drug management agency has its unique drug data management needs, and the steps and methods of obtaining the target set of traditional Chinese medicine information in the embodiment are taken as optional conditions, which can ensure that the embodiment can flexibly adapt to these different needs, and can ensure that the traditional Chinese medicine information set matches the actual needs of the hospital.

[0095] S3, set the reference evaluation index of traditional Chinese medicine data, obtain the 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. The specific steps and implementation contents are as follows:

[0096] The reference evaluation index of traditional Chinese medicine data is set based on the historical traditional Chinese medicine management data of the hospital. In the embodiment, the above-mentioned reference evaluation index mainly includes 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, data rationality and data security.

[0097] In the embodiment, the reference evaluation index of traditional Chinese medicine data is mainly set based on the historical traditional Chinese medicine management data of the hospital, which provides a clear direction for the optimization of the traditional Chinese medicine data management system. The above-mentioned index not only includes key aspects such as data transmission, data rationality and data security, but also through specific quantitative standards, the adjustment and optimization of the traditional Chinese medicine time-feature information set are more reliable.

[0098] The reference evaluation index is analyzed.

[0099] The data transmission efficiency can calculate the ratio of the received data number to the received data number, and then measure the efficiency of the hospital traditional Chinese medicine data in the transmission process. The above-mentioned data transmission efficiency satisfies the following relationship:

[0100]

[0101] Wherein, represents the transmission rate of all traditional Chinese medicine data in any time series, represents the sum of the received data number of each data type in the monitoring period, represents the sum of the received data number of each data type in the monitoring period.

[0102] 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 data analysis and management decision basis for the management method of traditional Chinese medicine data.

[0103] The data rationality index mainly focuses on the logicality and consistency of traditional Chinese medicine data, ensures that there is no error or exception in the input, processing and storage process of traditional Chinese medicine data, and through setting reasonable data checking rules and exception detection mechanism, the unreasonable places in the data can be found and corrected in time, improving the accuracy and reliability of the data.

[0104] Data security indicators need to emphasize the confidentiality, integrity and availability of traditional Chinese medicine data in the process of storage, transmission and use. Through the management method of traditional Chinese medicine data, encryption technology, access control, data backup and recovery and other measures can effectively protect traditional Chinese medicine data from unauthorized access, tampering and loss and other risks.

[0105] In an optional embodiment, the traditional Chinese medicine time-feature information set is further adjusted and optimized based on the reference evaluation indicators of traditional Chinese medicine data.

[0106] Based on the above reference evaluation indicators, the traditional Chinese medicine time-feature information set is adjusted and optimized by the traditional Chinese medicine data management system as follows: based on the data transmission efficiency, the data transmission efficiency is further improved. The data transmission protocol and channel in the traditional Chinese medicine data management system are optimized to reduce the delay and packet loss of traditional Chinese medicine data in the transmission process, while the transmission monitoring and alarm mechanism of traditional Chinese medicine data is strengthened to timely discover and solve the related problems of traditional Chinese medicine data in the transmission system.

[0107] According to the rationality test results, the rationality verification process of traditional Chinese medicine data in the system is enhanced. The data verification rules and abnormal detection mechanism in the traditional Chinese medicine data management system are improved to ensure the logicality and consistency of traditional Chinese medicine data, and the quality of traditional Chinese medicine data information is checked and evaluated regularly to timely discover and correct unreasonable places in the system data. On the other hand, the data security is strengthened, the advanced encryption technology and access control strategy are adopted in the traditional Chinese medicine data management system to protect the confidentiality and integrity of traditional Chinese medicine data, and a perfect traditional Chinese medicine data backup and recovery mechanism is established to ensure that traditional Chinese medicine data can be recovered in time when facing risks.

[0108] In summary, by setting the reference evaluation indicators of traditional Chinese medicine data based on the historical traditional Chinese medicine management data of the hospital, and adjusting and optimizing the traditional Chinese medicine time-feature information set according to the related indicators, the efficiency and quality of traditional Chinese medicine data management can be significantly improved, which is helpful for the reasonable layout of traditional Chinese medicine data management decision, and is conducive to the scientific development of traditional Chinese medicine clinical application and digital medical treatment.

[0109] Further, the method of adjusting and optimizing the traditional Chinese medicine information set in this embodiment is only an optional condition of this embodiment, and in other one or some embodiments, the optimization and adjustment method of traditional Chinese medicine information set can be replaced according to the hospital drug data management demand and traditional Chinese medicine data management target. Different hospitals or data management institutions have different data management demands and targets, and the method of adjusting and optimizing traditional Chinese medicine database can ensure that the data management scheme can meet the current diversified demands, so as to improve the operation efficiency and implementation effect of traditional Chinese medicine data management method.

[0110] S4, based on the target set of traditional Chinese medicine information, the use of traditional Chinese medicine in the hospital is analyzed to manage and monitor the use of traditional Chinese medicine data and use, and the specific steps and implementation contents are as follows:

[0111] Based on the target set of traditional Chinese medicine information, the use of traditional Chinese medicine in the hospital is analyzed to manage and monitor the use of traditional Chinese medicine data and use, and the specific steps and implementation contents are as follows:

[0112] The reference traditional Chinese medicine information set, the traditional Chinese medicine historical management data set and the traditional Chinese medicine use specification information are compared with the traditional Chinese medicine information target set to check whether the traditional Chinese medicine use in the hospital conforms to the specification and whether there is abnormal use of medicine.

[0113] A kind of traditional Chinese medicine data management method based on big data can also use statistical analysis, data mining and other methods to analyze traditional Chinese medicine data, and reveal the existing trend of traditional Chinese medicine, commonly used traditional Chinese medicine, drug compatibility and other information.

[0114] According to the above traditional Chinese medicine use data and use, the problem identification and report analysis are carried out.

[0115] According to the analysis result of traditional Chinese medicine information, potential problems such as unreasonable use of traditional Chinese medicine, drug abuse and drug shortage are identified, and detailed traditional Chinese medicine use analysis report is generated, including but not limited to problem summary, cause analysis, suggestion measures, etc., for the reference of hospital management and relevant departments.

[0116] A kind of traditional Chinese medicine data management method based on big data also includes monitoring and feedback mechanism.

[0117] The traditional Chinese medicine data management method of the embodiment also integrates big data technology and monitoring feedback mechanism. Based on this, a monitoring system of traditional Chinese medicine data and use can be constructed. The above system can track and analyze the dynamic change of traditional Chinese medicine use data in real time. If any data anomaly or deviation from the expected situation is found, the system will immediately send feedback information to the relevant departments and responsible persons, so as to take necessary traditional Chinese medicine information adjustment measures quickly.

[0118] In practical application, a kind of traditional Chinese medicine data management method based on big data covers the following key steps:

[0119] The improvement of traditional Chinese medicine information target set: in order to ensure the comprehensiveness and accuracy of traditional Chinese medicine data, an accurate and effective traditional Chinese medicine information library is constructed. The above information not only contains the basic information of traditional Chinese medicine such as name, efficacy, usage and dosage, but also covers the key contents such as traditional Chinese medicine compatibility, contraindication and measurement, which lays a solid foundation for subsequent traditional Chinese medicine data management and analysis.

[0120] Selection of Traditional Chinese Medicine Data Analysis Tools: According to the actual situation of the hospital and the demand of drug data management, efficient data analysis tools and methods such as SPSS, SAS, Python, etc. can be selected to further improve the accuracy of traditional Chinese medicine information analysis results and the smoothness of related system operation.

[0121] Establishment of Hospital Multi-department Cooperation Mechanism: In order to promote the comprehensive collection, in-depth analysis and continuous improvement of traditional Chinese medicine drug use data, strengthen the communication and cooperation among multiple departments such as hospital pharmacy, traditional Chinese medicine clinical department and traditional Chinese medicine information department, and form a mutual cooperation and coordination mechanism.

[0122] Through the above measures and specific implementation schemes, it is helpful to realize the comprehensive, systematic understanding, monitoring and management of traditional Chinese medicine drug use in the hospital, to timely find and correct the problems in the process of traditional Chinese medicine drug use, so as to ensure the rationality, safety and effectiveness of traditional Chinese medicine drug use. At the same time, it provides strong technical support for scientific management and real-time monitoring of traditional Chinese medicine drug use data in the hospital, and promotes the overall improvement of traditional Chinese medicine drug use management level and actual application effect in the hospital.

[0123] Please refer to Figure 3 In an optional embodiment, in order to efficiently execute the management method of traditional Chinese medicine data based on big data provided by the present application, the present application also provides a management system of traditional Chinese medicine data based on big data, which comprises a processor, an input device, an output device and a memory, which are connected with each other. The memory is used to store a computer program, the computer program comprises program instructions, and the processor is configured to call the program instructions to execute the specific steps of the embodiments of the management method of traditional Chinese medicine data based on big data provided by the present application. The management system of traditional Chinese medicine data based on big data of the present application has complete structure and objective stability, can efficiently execute the management method of traditional Chinese medicine data based on big data of the present application, and improves the overall applicability and practical application ability of the present application.

[0124] Finally, it should be pointed out that: the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and 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 application, and they should be covered in the scope of the claims and description of the present application.

Claims

1. A method for managing traditional Chinese medicine data based on big data, characterized in that, The method comprises the following steps: obtaining a traditional Chinese medicine management database through a traditional Chinese medicine data management system of a hospital; 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; setting a reference evaluation index of 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 by the traditional Chinese medicine data management system, so as to obtain a traditional Chinese medicine information target set; analyzing the traditional Chinese medicine medication situation of the hospital based on the traditional Chinese medicine information target set, so as to manage and monitor the traditional Chinese medicine medication data and use situation of the hospital; the data management optimization model is established according to the traditional Chinese medicine management database, which comprises: introducing a time series analysis method and a fuzzy mean clustering method; the 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, which comprises: analyzing the traditional Chinese medicine management database by using the time series analysis method, and obtaining a time series-traditional Chinese medicine data set of the traditional Chinese medicine management database, wherein the time series-traditional Chinese medicine data set comprises each time series information in different time series; extracting feature information of traditional Chinese medicine data based on the traditional Chinese medicine management database; obtaining a time series feature data matrix by combining the time series-traditional Chinese medicine data set and the feature information; ， wherein, denotes a matrix of time series feature data, denotes the i-th feature data in the j-th time series, denotes the i-th feature data in the j-th time series, denotes the i-th feature data in the j-th time series, analyzing the membership degree and feature distance of different time series features in the time series feature data matrix by using the fuzzy mean clustering method; the membership degree comprises setting the number of clusters according to the dynamic characteristics and management requirements of the traditional Chinese medicine database, generating a membership matrix based on the number of clusters, obtaining an initial cluster center according to the number of clusters, and analyzing the membership degree of the membership matrix according to the initial cluster center; the data management optimization model is established based on the membership degree, the feature distance and the fuzzy mean clustering method; the time series feature data matrix is optimized by using the data management optimization model, so as to obtain a traditional Chinese medicine time-feature information set, and the data management optimization model satisfies the following relationship: ， wherein, denotes the information of the time feature of the medicine after optimization, denotes the minimized objective function, denotes the membership of the th feature data point of the th time series to the cluster center, denotes the fuzzy coefficient obtained based on the fuzzy mean clustering method, denotes the weighted feature distance between the th feature data point of the th time series after optimization and the corresponding cluster center. 2.The big data-based traditional Chinese medicine data management method according to claim 1, characterized in that, the traditional Chinese medicine management database is obtained through the traditional Chinese medicine data management system of the hospital, which comprises: setting a data remote monitoring module, a data remote recording module and a data distribution monitoring module in the traditional Chinese medicine data management system; obtaining traditional Chinese medicine dynamic management data of the hospital through the data remote monitoring module; receiving and recording the traditional Chinese medicine dynamic management data through the data remote recording module; analyzing the state of the traditional Chinese medicine dynamic management data through the data distribution monitoring module, and obtaining a traditional Chinese medicine management database based on the state analysis result.

3. A big data-based traditional Chinese medicine data management system, characterized in that, The system comprises a processor, an input device, an output device and a memory, which are connected to each other, wherein the memory is used to store a computer program, the computer program comprises program instructions, the processor is configured to call the program instructions, and execute the management method of traditional Chinese medicine data based on big data according to any one of claims 1-2.

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