Traditional Chinese medicine quality data management and control method and system based on data mining

Abstract

The invention relates to the field of traditional Chinese medicine quality control, in particular to a traditional Chinese medicine quality data control method and system based on data mining. The method comprises the following steps: acquiring a historical traditional Chinese medicine prescription data set of a medical case information management platform, arranging various sensors at traditional Chinese medicine production process equipment, acquiring historical production data of the historical traditional Chinese medicine prescription data set through each sensor, analyzing the historical traditional Chinese medicine prescription data set and the historical production data, and determining the traditional Chinese medicine prescription data set. Establishing a prescription production data tree; analyzing the prescription production data tree and the historical traditional Chinese medicine prescription data set, and establishing a traditional Chinese medicine quality data chain; analyzing the traditional Chinese medicine quality data chain in combination with the prescription production data tree, and establishing a traditional Chinese medicine quality control data chain; and acquiring real-time traditional Chinese medicine prescription data, and analyzing the real-time traditional Chinese medicine prescription data in combination with the traditional Chinese medicine quality control data link to obtain a traditional Chinese medicine quality control scheme. The traditional Chinese medicine quality control efficiency and precision can be improved.

Description

Technical Field

[0001] This invention relates to the field of quality control of traditional Chinese medicine, and specifically to a method and system for quality data control of traditional Chinese medicine based on data mining. Background Technology

[0002] With the accelerated modernization and internationalization of traditional Chinese medicine (TCM), the production of TCM is transforming from traditional workshop-style production to industrialized and large-scale operations, significantly increasing the requirements for quality consistency across the entire industry chain (planting, harvesting, processing, preparation, storage, and distribution). For example, the promotion of GAP (Good Agricultural Practices) for medicinal materials requires strict control over the planting environment (soil, climate, pesticide residues) and processing techniques. The rapid development of modern information technology, especially big data, artificial intelligence, and data mining technologies, has provided new technological pathways for the quality control of TCM.

[0003] Chinese patent CN116630317A discloses an online quality monitoring method for traditional Chinese medicine decoction pieces, comprising: acquiring images of traditional Chinese medicine decoction pieces; performing grayscale conversion and Gaussian filtering on the acquired images; performing full threshold segmentation on the processed images to obtain the foreground and background parts of the images; performing grid processing on the foreground part of the images and constructing a two-dimensional coordinate system for the area where the grid is located; calculating the distance between a vertex and other vertices in the same grid; performing preliminary screening based on the distance between grid vertices; and performing a second screening of traditional Chinese medicine decoction pieces based on an area threshold.

[0004] In existing technologies, traditional Chinese medicine quality control methods rely heavily on experience-based judgment, physicochemical index testing, and qualitative and quantitative analysis of a small number of components. These methods cannot fully reflect the intrinsic quality of Chinese medicine as a whole and suffer from problems such as incomplete data, low information utilization, and difficulty in dynamic traceability. These are problems that we need to solve. Summary of the Invention

[0005] The purpose of this invention is to address the problems existing in the background technology by proposing a data mining-based method for quality data management of traditional Chinese medicine.

[0006] The technical solution of this invention: A method for quality data management of traditional Chinese medicine based on data mining, comprising the following steps:

[0007] S1. Obtain historical Chinese medicine prescription datasets from the medical record information management platform. Install various sensors at the Chinese medicine production process equipment and acquire historical production data from the historical Chinese medicine prescription datasets through each sensor. Analyze the historical Chinese medicine prescription datasets and historical production data to establish a prescription production data tree. Analyze the prescription production data tree and historical Chinese medicine prescription datasets to establish a Chinese medicine quality data chain.

[0008] S2. Combine the data tree of prescription production to analyze the data chain of traditional Chinese medicine quality and establish a data chain for the quality control of traditional Chinese medicine.

[0009] S3. Obtain real-time Chinese medicine prescription data, analyze the real-time Chinese medicine prescription data in conjunction with the Chinese medicine quality control data chain, and obtain a Chinese medicine quality control plan.

[0010] Preferably, the process of establishing the prescription production data tree includes:

[0011] The historical Chinese medicine prescription dataset includes the composition of historical prescriptions and Chinese medicine data;

[0012] The historical production data includes historical production time, historical core processes, and historical process data; the historical process data includes historical production parameter data and historical process spectrum diagrams.

[0013] Based on the number of historical Chinese medicine prescription datasets, several prescription nodes are constructed. Multiple prescription nodes with consistent historical prescription composition are merged into a single prescription multi-source node. This merging process is repeated until no more prescription nodes remain. The names of all Chinese herbs in the historical prescriptions are input into the prescription multi-source node. Production slave nodes are generated based on the historical production time consistent with the historical prescription composition. The historical production time is input into the production slave node, and the weight of the Chinese herbs in the historical prescription composition is obtained. The weight ratios among the components of the historical prescriptions are recorded as the Chinese herb ratio and input into the production slave node. Process sub-nodes are constructed based on the historical process data of the historical production time. Historical process data is input into the process sub-nodes according to the historical core process. Process sub-nodes with the same historical production time are associated according to the flow order of the historical core process, and the first process of the historical core process is associated with the production slave node to obtain the prescription production data tree.

[0014] Preferably, the process of establishing the traditional Chinese medicine quality data chain includes:

[0015] Data mining techniques were used to obtain the Chinese herbal ingredients and their corresponding Chinese herbal names from historical Chinese herbal prescription datasets.

[0016] By combining infrared spectroscopy technology, the historical process spectral maps of each process sub-node of the prescription production data tree are compared and matched with the spectral database to obtain the process component spectral maps of Chinese medicine ingredients. Combined with standard content data, the process component spectral maps are analyzed through metrological algorithms to obtain the content of process components and historical processes.

[0017] Construct process quality data nodes by grouping the contents of Chinese herbal ingredients and process components into the process quality data nodes, and set up associated process data lines between the process quality data nodes and the corresponding process sub-nodes; connect each process quality data node with the associated process data lines, and set up associated time data lines between the process quality data nodes and the production slave nodes of the prescription production data tree to obtain the Chinese herbal quality data chain of the prescription production data tree.

[0018] Preferably, the process of establishing the traditional Chinese medicine quality control data chain includes:

[0019] Group the production nodes corresponding to the same proportion of Chinese medicine in the prescription production data tree into a group to obtain the same production proportion group. Group the process quality data nodes corresponding to the same historical process in the Chinese medicine quality data chain associated with the same production proportion group into a group to obtain the same process quality group.

[0020] Set a process quality threshold; if the total number of process quality data nodes corresponding to the same content of Chinese herbal medicine components in each process quality data node of the same process quality group is greater than or equal to the process quality threshold, then mark the process quality data node to obtain the Chinese herbal medicine component label; if the total number of process quality data nodes corresponding to the same content of Chinese herbal medicine components is less than the process quality threshold, mark the process sub-nodes that have associated process data lines with the process quality data nodes as closed process sub-nodes.

[0021] Preferably, the process of establishing the traditional Chinese medicine quality control data chain further includes:

[0022] Obtain the maximum and minimum values ​​of historical production parameter data within the process sub-nodes that are associated with the process quality data nodes containing all Chinese herbal medicine ingredient markers;

[0023] Calculate the average of the maximum and minimum values ​​of each historical production parameter data to obtain the range of each production parameter. Mark the process sub-nodes involved in the calculation as closed process sub-nodes. Generate TCM process production slave nodes based on each production parameter range. Generate TCM ratio sub-nodes based on the TCM ratio of the same production ratio group. Associate the TCM ratio sub-nodes with the corresponding prescription multi-source nodes. Associate the TCM process production slave nodes with each other according to the historical processes of the same process quality group. Associate the TCM process production slave nodes with the TCM ratio sub-nodes. Repeat the operation of obtaining production parameter ranges until all process sub-nodes are marked as closed process sub-nodes. Construct a TCM quality control data chain through prescription multi-source nodes, TCM ratio sub-nodes, and TCM process production slave nodes.

[0024] Preferably, the process of analyzing real-time traditional Chinese medicine (TCM) prescription data by combining a TCM quality control data chain to obtain a TCM quality control plan includes:

[0025] Acquire real-time traditional Chinese medicine prescription data, which includes real-time prescription composition and real-time proportion of traditional Chinese medicine;

[0026] By traversing the TCM quality control data chain based on real-time prescription composition and real-time TCM proportions, if the TCM names of the multi-source nodes of the prescription do not completely include the TCM names of the real-time prescription composition, multiple multi-source nodes of prescriptions are obtained. The intersection interval of the production parameter intervals of each TCM process of each historical process associated with multiple multi-source nodes of prescriptions is recorded as the TCM quality control interval. The production parameters of the TCM production process related to the real-time TCM prescription data are controlled within the corresponding TCM quality control interval to obtain the TCM quality control scheme.

[0027] Preferably, the process of analyzing real-time traditional Chinese medicine prescription data by combining the traditional Chinese medicine quality control data chain to obtain a traditional Chinese medicine quality control plan also includes:

[0028] If the names of Chinese medicines in the multi-source nodes of the prescription completely contain the names of Chinese medicines in the real-time prescription, and the proportion of Chinese medicines in the real-time prescription completely matches the proportion of Chinese medicines in the proportion sub-node, then the production parameters in the production process related to the real-time prescription data will be controlled within the corresponding production parameter range through all production parameter ranges in the production process of Chinese medicines associated with the proportion sub-node, thereby obtaining a Chinese medicine quality control plan.

[0029] If the names of Chinese herbs in the multi-source nodes of the prescription completely contain the names of Chinese herbs in the real-time prescription, and the proportion of Chinese herbs in the real-time prescription does not completely match the proportion of Chinese herbs in the proportion sub-nodes, then multiple proportion sub-nodes of Chinese herbs associated with the multi-source nodes of the prescription are obtained. The intersection of the production parameter ranges of each production process of each Chinese herbal medicine production sub-node associated with each historical process of multiple proportion sub-nodes of Chinese herbs is recorded as the production quality control range. The production parameters in the Chinese herbal medicine production process related to the real-time Chinese herbal medicine prescription data are controlled within the corresponding production quality control range to obtain the Chinese herbal medicine quality control plan.

[0030] This invention also discloses a data mining-based traditional Chinese medicine quality data management and control system, including a management center, which is communicatively connected to a traditional Chinese medicine data acquisition and analysis module, a traditional Chinese medicine data processing module, and a traditional Chinese medicine quality management and control module.

[0031] The traditional Chinese medicine (TCM) data acquisition and analysis module is used to acquire historical TCM prescription datasets from the medical record information management platform. Multiple sensors are installed at the TCM production process equipment to acquire historical production data from the historical TCM prescription datasets. The module analyzes the historical TCM prescription datasets and historical production data to establish a prescription production data tree. The module also analyzes the prescription production data tree and historical TCM prescription datasets to establish a TCM quality data chain.

[0032] The traditional Chinese medicine data processing module is used to analyze the traditional Chinese medicine quality data chain by combining the prescription production data tree and establishing a traditional Chinese medicine quality control data chain.

[0033] The Traditional Chinese Medicine (TCM) quality control module is used to acquire real-time TCM prescription data, analyze the real-time TCM prescription data in conjunction with the TCM quality control data chain, and obtain TCM quality control solutions.

[0034] Compared with the prior art, the above-mentioned technical solution of the present invention has the following beneficial technical effects: Analysis of historical Chinese medicine prescription datasets and historical production data to establish a prescription production data tree; analysis of the prescription production data tree and historical Chinese medicine prescription datasets to establish a Chinese medicine quality data chain, realizing the modeling and visual tracking of the Chinese medicine quality production process, improving the efficiency and accuracy of Chinese medicine quality analysis; analysis of the Chinese medicine quality data chain in conjunction with the prescription production data tree to establish a Chinese medicine quality control data chain, realizing the mapping between Chinese medicine production parameters and quality, supporting matching between multiple prescriptions, and improving the universality of Chinese medicine quality control; acquisition of real-time Chinese medicine prescription data, analysis of real-time Chinese medicine prescription data in conjunction with the Chinese medicine quality control data chain to obtain a Chinese medicine quality control scheme, improving the stability and consistency of Chinese medicine quality, improving the standardization of the Chinese medicine production process, and improving the efficiency and accuracy of Chinese medicine quality control. Attached Figure Description

[0035] Figure 1 This is a flowchart of one embodiment of the present invention. Detailed Implementation

[0036] Example 1, as Figure 1 As shown, the present invention proposes a method for quality data management of traditional Chinese medicine based on data mining, which includes the following steps:

[0037] S1. Obtain historical Chinese medicine prescription datasets from the medical record information management platform. Install various sensors at the Chinese medicine production process equipment and acquire historical production data from the historical Chinese medicine prescription datasets through each sensor. Analyze the historical Chinese medicine prescription datasets and historical production data to establish a prescription production data tree. Analyze the prescription production data tree and historical Chinese medicine prescription datasets to establish a Chinese medicine quality data chain.

[0038] S2. Combine the data tree of prescription production to analyze the data chain of traditional Chinese medicine quality and establish a data chain for the quality control of traditional Chinese medicine.

[0039] S3. Obtain real-time Chinese medicine prescription data, analyze the real-time Chinese medicine prescription data in conjunction with the Chinese medicine quality control data chain, and obtain a Chinese medicine quality control plan.

[0040] It needs further explanation that, in the specific implementation process, the historical Chinese medicine prescription dataset is obtained from the medical record information management platform. Multiple sensors are installed at the Chinese medicine production equipment to acquire historical production data from the historical Chinese medicine prescription dataset. The historical Chinese medicine prescription dataset and historical production data are analyzed to establish a prescription production data tree. The process of analyzing the prescription production data tree and the historical Chinese medicine prescription dataset to establish a Chinese medicine quality data chain is as follows:

[0041] The historical Chinese medicine prescription dataset includes the composition of historical prescriptions and Chinese medicine data;

[0042] Specifically, the composition of historical prescriptions refers to the names of the Chinese herbs that make up the historical prescriptions, and the Chinese herbal data refers to the Chinese herbal data corresponding to the names of the Chinese herbs that make up the prescriptions, including but not limited to theoretical data, classification, and pharmacology.

[0043] The various sensors include, but are not limited to, temperature sensors, humidity sensors, infrared sensors, pressure sensors, and weighing sensors; the historical production data includes historical production time, historical core processes, and historical process data; the historical process data includes historical production parameter data and historical process spectrum diagrams.

[0044] Specifically, to ensure the comparability of historical process data collected by various sensors, the number of Chinese medicine production equipment corresponding to each historical core process is equal.

[0045] Based on the number of historical Chinese medicine prescription datasets, construct several prescription nodes. Merge multiple prescription nodes with consistent historical prescription composition into a single prescription multi-source node. Repeat the merging operation until no prescription nodes remain. Input the names of all Chinese herbs in the historical prescriptions into the prescription multi-source node. Generate production slave nodes based on the historical production time consistent with the historical prescription composition. Input the historical production time into the production slave node and obtain the weight of Chinese herbs in the historical prescription composition. Record the weight ratio between the components of the historical prescription as the Chinese herb ratio and input it into the production slave node. Construct process sub-nodes based on the historical process data of the historical production time. Input the historical process data into the process sub-nodes according to the historical core process. Associate the process sub-nodes with the same historical production time according to the process sequence of the historical core process. Associate the first process of the historical core process with the production slave node to obtain the prescription production data tree.

[0046] Specifically, if the historical Chinese medicine prescription dataset in the medical record information management platform is updated, the updated historical Chinese medicine prescription dataset will be updated in the prescription production data tree through the above steps. Therefore, the prescription production data tree is constantly being updated.

[0047] Data mining techniques are used to obtain the Chinese herbal medicine components and their corresponding Chinese herbal medicine names from historical Chinese herbal medicine prescription datasets corresponding to historical production times; the Chinese herbal medicine components include marker components and active ingredients.

[0048] By combining infrared spectroscopy technology, the historical process spectra of each process sub-node in the prescription production data tree are compared and matched with the spectral database to obtain the process component spectra of traditional Chinese medicine ingredients. Combined with standard content data, the process component spectra are analyzed using metrological algorithms to obtain the process component content and historical process; the process component content includes the content of marker components and the content of active ingredients.

[0049] Specifically, the spectral database and standard content data are existing data in the relevant fields;

[0050] Construct process quality data nodes by grouping the contents of Chinese herbal ingredients and process components into the process quality data nodes, and set up a process data line between the process quality data nodes and the corresponding process sub-nodes; combine the process data lines, connect each process quality data node according to the order of the process sub-nodes, and set up a time data line between the first process quality data node and the production slave node of the prescription production data tree to obtain the Chinese herbal quality data chain of the prescription production data tree.

[0051] It should be further explained that, in the specific implementation process, the process of analyzing the TCM quality data chain and establishing the TCM quality control data chain by combining the prescription production data tree is as follows:

[0052] Group the production nodes corresponding to the same proportion of Chinese medicine in the prescription production data tree into a group to obtain the same production proportion group. Group the process quality data nodes corresponding to the same historical process in the Chinese medicine quality data chain associated with the same production proportion group into a group to obtain the same process quality group.

[0053] Set a process quality threshold, which is less than the total number of nodes in the same process quality group; sequentially obtain the content of the same Chinese herbal medicine component for each process quality data node in the same process quality group; if the total number of process quality data nodes corresponding to the same content of the same Chinese herbal medicine component is greater than or equal to the process quality threshold, then mark the process quality data node to obtain the Chinese herbal medicine component label; if the total number of process quality data nodes corresponding to the same content of the same Chinese herbal medicine component is less than the process quality threshold, then the process quality data node is not marked, and the process sub-nodes that have associated process data lines with the process quality data nodes are marked as closed process sub-nodes;

[0054] Specifically, the labeling of Chinese medicine components refers to the name of the corresponding Chinese medicine component. The name of the Chinese medicine component is labeled in the process quality data node. In the above steps, the labeling of Chinese medicine components is not overwritten and is fully recorded in the process quality node.

[0055] Obtain the maximum and minimum values ​​of historical production parameter data within the process sub-nodes that are associated with the process quality data nodes containing all Chinese herbal medicine ingredient markers;

[0056] Specifically, obtaining the maximum and minimum values ​​refers to the maximum and minimum values ​​of each historical production parameter data within each process sub-node. The historical production parameter data includes, but is not limited to, temperature, humidity, and pressure, and the historical production parameter data of different process sub-nodes are not completely the same.

[0057] Calculate the average of the maximum and minimum values ​​of each historical production parameter data to obtain the range of each production parameter. Mark the process sub-nodes involved in the calculation as closed process sub-nodes. Generate TCM process production slave nodes based on each production parameter range. Generate TCM ratio sub-nodes based on the TCM ratio of the same production ratio group. Associate the TCM ratio sub-nodes with the corresponding prescription multi-source nodes. Associate each TCM process production slave node with the historical process of the same process quality group. Associate the first TCM process production slave node with the TCM ratio sub-node. Repeat the operation of obtaining production parameter ranges until all process sub-nodes are marked as closed process sub-nodes. Construct a TCM quality control data chain through prescription multi-source nodes, TCM ratio sub-nodes, and TCM process production slave nodes.

[0058] It should be further explained that, in the specific implementation process, the process of acquiring real-time TCM prescription data, analyzing the real-time TCM prescription data in conjunction with the TCM quality control data chain, and obtaining the TCM quality control plan is as follows:

[0059] Acquire real-time traditional Chinese medicine prescription data, which includes real-time prescription composition and real-time proportion of traditional Chinese medicine;

[0060] By traversing the TCM quality control data chain through real-time prescription composition and real-time TCM ratio, if the TCM names of the multi-source nodes of the prescription do not completely contain the TCM names of the real-time prescription composition, multiple multi-source nodes of prescription are obtained. The intersection interval of the production parameter intervals of each TCM process of each historical process associated with multiple multi-source nodes of prescription is recorded as the TCM quality control interval. The production parameters of the TCM production process related to the real-time TCM prescription data are controlled within the corresponding TCM quality control interval, and the production parameters are kept as stable as possible to obtain the TCM quality control scheme.

[0061] Specifically, the historical prescription composition of multiple prescription multi-source nodes contains Chinese medicine names that overlap with the real-time prescription composition. The historical prescription composition of multiple prescription multi-source nodes includes all real-time prescription compositions. The Chinese medicine names that overlap in the historical prescription composition of multiple prescription multi-source nodes are all within the real-time prescription composition, and the Chinese medicine ratio of the Chinese medicine ratio sub-node corresponding to the overlapping Chinese medicine name is consistent with the real-time Chinese medicine ratio.

[0062] If the names of Chinese herbs in the multi-source nodes of the prescription completely contain the names of Chinese herbs in the real-time prescription, and the proportion of Chinese herbs in the real-time prescription completely matches the proportion of Chinese herbs in the proportion sub-node, then the production parameters in the production process related to the real-time prescription data will be controlled within the corresponding production parameter range through all production parameter ranges within the node of the Chinese herbal medicine production process associated with the proportion sub-node, and the stability of the production parameters will be maintained as much as possible, so as to obtain a Chinese herbal medicine quality control plan.

[0063] If the names of Chinese herbs in the multi-source nodes of the prescription completely contain the names of Chinese herbs in the real-time prescription, and the proportion of Chinese herbs in the real-time prescription does not completely match the proportion of Chinese herbs in the proportion sub-nodes, then multiple proportion sub-nodes of Chinese herbs associated with the multi-source nodes of the prescription are obtained. The intersection of the production parameter ranges of each production process of each historical process associated with the multiple proportion sub-nodes of Chinese herbs is recorded as the production quality control range. The production parameters corresponding to the production process of Chinese herbs related to the real-time prescription data are controlled within the corresponding production quality control range, and the production parameters are kept as stable as possible to obtain a Chinese herbs quality control scheme.

[0064] Specifically, some Chinese medicine proportions in the Chinese medicine proportion sub-nodes are consistent with the real-time Chinese medicine proportions, and the Chinese medicine proportions of multiple Chinese medicine proportion sub-nodes include all real-time Chinese medicine proportions.

[0065] Example 2: The traditional Chinese medicine quality data management system based on data mining proposed in this invention is applied to the traditional Chinese medicine quality data management method based on data mining described in Example 1. Specifically, it includes a management center, which is communicatively connected to a traditional Chinese medicine data acquisition and analysis module, a traditional Chinese medicine data processing module, and a traditional Chinese medicine quality management module.

[0066] The traditional Chinese medicine (TCM) data acquisition and analysis module is used to acquire historical TCM prescription datasets from the medical record information management platform. Multiple sensors are installed at the TCM production process equipment to acquire historical production data from the historical TCM prescription datasets. The module analyzes the historical TCM prescription datasets and historical production data to establish a prescription production data tree. The module also analyzes the prescription production data tree and historical TCM prescription datasets to establish a TCM quality data chain.

[0067] The traditional Chinese medicine data processing module is used to analyze the traditional Chinese medicine quality data chain by combining the prescription production data tree and establishing a traditional Chinese medicine quality control data chain.

[0068] The Traditional Chinese Medicine (TCM) quality control module is used to acquire real-time TCM prescription data, analyze the real-time TCM prescription data in conjunction with the TCM quality control data chain, and obtain TCM quality control solutions.

[0069] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A method for quality data management and control of traditional Chinese medicine based on data mining, characterized in that, Includes the following steps: S1. Obtain historical Chinese medicine prescription datasets from the medical record information management platform. Set up multiple sensors at the Chinese medicine production process equipment and obtain historical production data of the historical Chinese medicine prescription datasets through each sensor. Analyze the historical Chinese medicine prescription datasets and historical production data to establish a prescription production data tree. Analyze the drug production data tree and historical Chinese medicine prescription datasets to establish a Chinese medicine quality data chain; S2. Combine the data tree of prescription production to analyze the data chain of traditional Chinese medicine quality and establish a data chain for the quality control of traditional Chinese medicine. S3. Obtain real-time Chinese medicine prescription data, analyze the real-time Chinese medicine prescription data in conjunction with the Chinese medicine quality control data chain, and obtain a Chinese medicine quality control plan.

2. The method for quality data management of traditional Chinese medicine based on data mining according to claim 1, characterized in that, The process of establishing the prescription production data tree includes: The historical Chinese medicine prescription dataset includes the composition of historical prescriptions and Chinese medicine data; The historical production data includes historical production time, historical core processes, and historical process data; the historical process data includes historical production parameter data and historical process spectrum diagrams. Based on the number of historical Chinese medicine prescription datasets, several prescription nodes are constructed. Multiple prescription nodes with consistent historical prescription composition are merged into a single prescription multi-source node. This merging process is repeated until no more prescription nodes remain. The names of all Chinese herbs in the historical prescriptions are input into the prescription multi-source node. Production slave nodes are generated based on the historical production time consistent with the historical prescription composition. The historical production time is input into the production slave node, and the weight of the Chinese herbs in the historical prescription composition is obtained. The weight ratios among the components of the historical prescriptions are recorded as the Chinese herb ratio and input into the production slave node. Process sub-nodes are constructed based on the historical process data of the historical production time. Historical process data is input into the process sub-nodes according to the historical core process. Process sub-nodes with the same historical production time are associated according to the flow order of the historical core process, and the first process of the historical core process is associated with the production slave node to obtain the prescription production data tree.

3. The method for quality data management of traditional Chinese medicine based on data mining according to claim 2, characterized in that, The process of establishing the traditional Chinese medicine quality data chain includes: Data mining techniques were used to obtain the Chinese herbal ingredients and their corresponding Chinese herbal names from historical Chinese herbal prescription datasets. By combining infrared spectroscopy technology, the historical process spectral maps of each process sub-node of the prescription production data tree are compared and matched with the spectral database to obtain the process component spectral maps of Chinese medicine ingredients. Combined with standard content data, the process component spectral maps are analyzed through metrological algorithms to obtain the content of process components and historical processes. Construct process quality data nodes by grouping the contents of Chinese herbal ingredients and process components into the process quality data nodes, and set up associated process data lines between the process quality data nodes and the corresponding process sub-nodes; connect each process quality data node with the associated process data lines, and set up associated time data lines between the process quality data nodes and the production slave nodes of the prescription production data tree to obtain the Chinese herbal quality data chain of the prescription production data tree.

4. The method for quality data management of traditional Chinese medicine based on data mining according to claim 3, characterized in that, The process of establishing the data chain for quality control of traditional Chinese medicine includes: Group the production nodes corresponding to the same proportion of Chinese medicine in the prescription production data tree into a group to obtain the same production proportion group. Group the process quality data nodes corresponding to the same historical process in the Chinese medicine quality data chain associated with the same production proportion group into a group to obtain the same process quality group. Set a process quality threshold; if the total number of process quality data nodes corresponding to the same content of Chinese herbal medicine components in each process quality data node of the same process quality group is greater than or equal to the process quality threshold, then mark the process quality data node to obtain the Chinese herbal medicine component label; if the total number of process quality data nodes corresponding to the same content of Chinese herbal medicine components is less than the process quality threshold, mark the process sub-nodes that have associated process data lines with the process quality data nodes as closed process sub-nodes.

5. The method for quality data management of traditional Chinese medicine based on data mining according to claim 4, characterized in that, The process of establishing the data chain for quality control of traditional Chinese medicine also includes: Obtain the maximum and minimum values ​​of historical production parameter data within the process sub-nodes that are associated with the process quality data nodes containing all Chinese herbal medicine ingredient markers; Calculate the average of the maximum and minimum values ​​of each historical production parameter data to obtain the range of each production parameter. Mark the process sub-nodes involved in the calculation as closed process sub-nodes. Generate TCM process production slave nodes based on each production parameter range. Generate TCM ratio sub-nodes based on the TCM ratio of the same production ratio group. Associate the TCM ratio sub-nodes with the corresponding prescription multi-source nodes. Associate the TCM process production slave nodes with each other according to the historical processes of the same process quality group. Associate the TCM process production slave nodes with the TCM ratio sub-nodes. Repeat the operation of obtaining production parameter ranges until all process sub-nodes are marked as closed process sub-nodes. Construct a TCM quality control data chain through prescription multi-source nodes, TCM ratio sub-nodes, and TCM process production slave nodes.

6. The method for quality data management of traditional Chinese medicine based on data mining according to claim 5, characterized in that, The process of analyzing real-time TCM prescription data by combining a TCM quality control data chain to obtain a TCM quality control plan includes: Acquire real-time traditional Chinese medicine prescription data, which includes real-time prescription composition and real-time proportion of traditional Chinese medicine; By traversing the TCM quality control data chain based on real-time prescription composition and real-time TCM proportions, if the TCM names of the multi-source nodes of the prescription do not completely include the TCM names of the real-time prescription composition, multiple multi-source nodes of prescriptions are obtained. The intersection interval of the production parameter intervals of each TCM process of each historical process associated with multiple multi-source nodes of prescriptions is recorded as the TCM quality control interval. The production parameters of the TCM production process related to the real-time TCM prescription data are controlled within the corresponding TCM quality control interval to obtain the TCM quality control scheme.

7. The method for quality data management of traditional Chinese medicine based on data mining according to claim 6, characterized in that, The process of analyzing real-time TCM prescription data by combining the TCM quality control data chain to obtain TCM quality control solutions also includes: If the names of Chinese medicines in the multi-source nodes of the prescription completely contain the names of Chinese medicines in the real-time prescription, and the proportion of Chinese medicines in the real-time prescription completely matches the proportion of Chinese medicines in the proportion sub-node, then the production parameters in the production process related to the real-time prescription data will be controlled within the corresponding production parameter range through all production parameter ranges in the production process of Chinese medicines associated with the proportion sub-node, thereby obtaining a Chinese medicine quality control plan. If the names of Chinese herbs in the multi-source nodes of the prescription completely contain the names of Chinese herbs in the real-time prescription, and the proportion of Chinese herbs in the real-time prescription does not completely match the proportion of Chinese herbs in the proportion sub-nodes, then multiple proportion sub-nodes of Chinese herbs associated with the multi-source nodes of the prescription are obtained. The intersection of the production parameter ranges of each production process of each Chinese herbal medicine production sub-node associated with each historical process of multiple proportion sub-nodes of Chinese herbs is recorded as the production quality control range. The production parameters in the Chinese herbal medicine production process related to the real-time Chinese herbal medicine prescription data are controlled within the corresponding production quality control range to obtain the Chinese herbal medicine quality control plan.

8. A data mining-based traditional Chinese medicine quality data management and control system, specifically applied to the data mining-based traditional Chinese medicine quality data management and control method described in any one of claims 1 to 7, comprising a management center, characterized in that, The management center's communication connections include a traditional Chinese medicine (TCM) data acquisition and analysis module, a TCM data processing module, and a TCM quality control module. The traditional Chinese medicine data acquisition and analysis module is used to acquire historical traditional Chinese medicine prescription datasets from the medical record information management platform. Multiple sensors are installed at the traditional Chinese medicine production process equipment to acquire historical production data of the historical traditional Chinese medicine prescription dataset through each sensor. The historical traditional Chinese medicine prescription dataset and historical production data are analyzed to establish a prescription production data tree. Analyze the drug production data tree and historical Chinese medicine prescription datasets to establish a Chinese medicine quality data chain; The traditional Chinese medicine data processing module is used to analyze the traditional Chinese medicine quality data chain by combining the prescription production data tree and establishing a traditional Chinese medicine quality control data chain. The Traditional Chinese Medicine (TCM) quality control module is used to acquire real-time TCM prescription data, analyze the real-time TCM prescription data in conjunction with the TCM quality control data chain, and obtain TCM quality control solutions.

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