Blood specimen storage management system for blood transfusion department

Abstract

The invention discloses a blood specimen storage management system for a blood transfusion department, and relates to the technical field of medical treatment, and the system comprises an integrated information collection module which is used for obtaining collection data, storage environment data, blood test data and blood use dynamic data of a blood specimen set in real time, generating a radio frequency identification tag code of the blood sample set; the blood specimen storage module is used for storing the collection data of the blood specimen set, the storage environment data, the blood test data and the blood use dynamic data in a preset medical storage space; the blood specimen query module is used for querying the storage position of the blood specimen set in the preset medical storage space in real time according to the radio frequency identification tag code of the blood specimen set; and the intelligent environment monitoring module is used for monitoring the temperature, humidity and illumination intensity of the storage position of the blood sample set.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to a blood specimen storage and management system for a blood transfusion department. Background Art

[0002] In the medical field, the blood transfusion department is responsible for the collection, processing and storage of blood specimens, which are essential for key medical procedures such as blood typing, antibody screening, cross-matching, etc. The management and use of blood specimens are directly related to patient safety and treatment effectiveness.

[0003] However, the current blood specimen storage and management system has significant difficulties in tracking, which has become an obstacle to improving the efficiency and safety of the blood transfusion department. Due to the lack of an effective electronic management system, the collection, processing and storage information of blood specimens is usually recorded in paper form, which makes it difficult to quickly retrieve the information. In an emergency, medical staff need to quickly find a specific blood specimen for testing or blood matching, but the inconvenience of paper records seriously delays this process and increases medical risks.

[0004] In summary, the difficulty in tracking blood specimens is an urgent problem to be solved. It not only affects the work efficiency of the blood transfusion department, but also concerns the life safety of patients. Summary of the invention

[0005] The embodiment of the present application provides a blood specimen storage and management system for a blood transfusion department to solve the above-mentioned technical problems.

[0006] The present application provides a blood sample storage management system for a blood transfusion department, comprising: an integrated information acquisition module, used to acquire the collection data, storage environment data, blood test data and blood usage dynamic data of a blood sample set in real time, and generate a wireless radio frequency identification tag code of the blood sample set; wherein the collection data includes collection time and collector information; the storage environment data includes storage time, storage location and storage requirements; a blood sample storage module, used to store the collection data, storage environment data, blood test data and blood usage dynamic data of the blood sample set in a preset medical storage space; a blood sample query module, used to query the storage location of the blood sample set in the preset medical storage space in real time according to the wireless radio frequency identification tag code of the blood sample set; an intelligent environment monitoring module, used to monitor the temperature, humidity and light intensity of the storage location of the blood sample set; a data analysis and decision support module, used to optimize the storage status of the blood sample set in the preset medical storage space.

[0007] Further, storing the collection data, storage environment data, blood test data, and blood usage dynamic data of the blood specimen set in a preset medical storage space includes: Create the preset medical storage space; For each blood specimen included in the blood specimen set, create a data encapsulation unit corresponding to the blood specimen; wherein, each data encapsulation unit includes collection data, storage environment data, blood test data, and blood usage dynamic data; each data encapsulation unit is assigned an identifier for being located in the preset medical storage space; Based on the attributes of the collection data, storage environment data, blood test data, and blood usage dynamic data, construct a hierarchical bounding volume tree; wherein, each data encapsulation unit corresponds to a node in the hierarchical bounding volume tree, and the bounding volume of the node includes the data characteristics of the data encapsulation unit; Store each data encapsulation unit in the hierarchical bounding volume tree.

[0008] Further, the constructing a hierarchical bounding volume tree based on the attributes of the collection data, storage environment data, blood test data, and blood usage dynamic data; and storing each data encapsulation unit in the hierarchical bounding volume tree includes: Determine the weight corresponding to each data encapsulation unit; Create the root node of the hierarchical bounding volume tree, and the bounding volume of the root node includes the logical spatial positions of the collection data, storage environment data, blood test data, and blood usage dynamic data; According to the attributes and weights of the data encapsulation units, allocate the data encapsulation units to the leaf nodes of the hierarchical bounding volume tree; In each node of the hierarchical bounding volume tree, use the key-value pair structure of the B-tree to manage the child nodes of each node.

[0009] Further, in each node included in the hierarchical bounding volume tree, for the non-leaf nodes of the hierarchical bounding volume tree, the key represents the boundary of the bounding volume of the child node, and the value represents the pointer to the child node; For the leaf nodes of the hierarchical bounding volume tree, the key represents the attributes of the data encapsulation unit, and the value represents the pointer to the data encapsulation unit; ; wherein, is the boundary of the bounding volume of a certain node in the hierarchical bounding volume tree; is the number of data encapsulation units included in this node; is the weight of the th data encapsulation unit; The weight of a data encapsulation unit; is the boundary of the bounding box of the th data encapsulation unit, where is the number of data encapsulation units; the min function is used to find the minimum value from a set of values; the max function is used to find the maximum value from a set of values.

[0010] Furthermore, optimizing the storage state of the blood specimen set in the preset medical storage space includes: Defining the optimization objectives for the storage state of the blood specimen set in the preset medical storage space; wherein, the optimization objectives include storage layout objectives, access efficiency objectives, environmental adaptability objectives, and data retrieval efficiency objectives; Initializing the population; wherein, each individual in the population contains two sets of genes, one set of genes represents the structure of the hierarchical bounding box tree, and the other set of genes represents the structure of the B-tree; Selecting individuals according to the proportion of the fitness value of the individual in the total fitness for crossover operation and mutation operation; wherein, the fitness value is evaluated based on the following indicators: storage layout, storage efficiency, environmental compliance, and storage proximity of data encapsulation units; After the crossover operation and the mutation operation are completed, select individuals with fitness higher than the fitness threshold from the final population; wherein, the individuals with fitness higher than the fitness threshold are the optimal combination of the hierarchical bounding box tree and the B-tree structure.

[0011] Furthermore, The storage layout is evaluated based on the following formula: ; wherein, represents the score of the storage layout, and the higher the value, the better the storage layout; represents the sum of the bounding box volumes of all nodes of the hierarchical bounding box tree; is the bounding box volume of the th node of the hierarchical bounding box tree; is the total number of nodes in the hierarchical bounding box tree; represents the total capacity of the preset medical storage space; The storage efficiency is evaluated based on the following formula: ; wherein, is the access speed score of the B-tree; is the maximum path length for accessing blood specimens; is the average path length for accessing blood specimens; is an adjustment parameter used to control the influence of the path length on the score.

[0012] Further, selecting individuals according to the proportion of the fitness value of an individual in the total fitness for performing crossover operation and mutation operation includes: Randomly select two parent hierarchical bounding box trees, and generate new offspring by exchanging partial subtrees or nodes; Randomly select two parent B-trees, and generate new offspring by exchanging key-value pairs or subtree structures; Randomly change the bounding box parameters of a node or the connection relationship of nodes; Randomly change the position of key-value pairs or modify the splitting strategy or merging strategy of nodes; Combine the offspring after crossover and mutation with the original population, select the optimal individuals according to the fitness value to form a new generation of population; repeat the crossover operation and mutation operation based on the new generation of population until there are individuals in the final population with a fitness higher than the fitness threshold.

[0013] Further, the blood test data includes the specimen type of blood, ABO blood type and RhD antigen typing information, blood routine information, coagulation function information, and antibody screening information; the specimen type includes venous whole blood specimen, arterial whole blood specimen, capillary whole blood specimen, plasma specimen, and serum specimen; The data analysis and decision support module is further configured to analyze the blood test data and storage environment data of the blood specimen set to generate cross-matching reference information for the blood specimen set.

[0014] Further, the blood specimen storage management system for the blood transfusion department further includes: A storage information backup module, configured to perform storage backup processing on the collection data, storage environment data, blood test data, and blood usage dynamic data of the blood specimen set to generate backup management information; A user interaction module, wirelessly connected to the blood specimen query module, for medical staff to input, query, and update the information of the blood specimens in the blood specimen set through voice or touch screen.

[0015] Further, the user interaction module includes an intelligent environment monitoring and prompting unit, and the intelligent environment monitoring and prompting unit is configured to display the temperature, humidity, and light intensity of the storage environment of the blood specimens in the blood specimen set, and display an alarm message when the temperature, humidity, or light intensity of the storage environment of the blood specimens does not meet the storage environment requirements of the blood specimens.

[0016] The present invention obtains the full-process data of blood specimens in real time through an integrated information collection module, including collection data, storage environment data, blood test data, and blood usage dynamic data, and generates a radio frequency identification tag code. This automated data collection and identification process significantly reduces the reliance on paper records, thereby improving the retrieval speed and accuracy of blood specimen information and optimizing the tracking and management efficiency of blood specimens. The intelligent environment monitoring module monitors the temperature, humidity, and light intensity of the storage location in real time to ensure that blood specimens are always stored under suitable conditions. The blood specimen query module can query the storage location of blood specimens in real time according to the radio frequency identification tag code, greatly shortening the time to find specific blood specimens in case of emergency. The data analysis and decision support module optimizes the storage status of the blood specimen collection, improving the utilization rate of the preset medical storage space. Transforming the collection, processing, and storage information of blood specimens from paper records to electronic management facilitates the long-term preservation, rapid retrieval, and sharing of information. This information-based management not only improves work efficiency but also provides data support for medical quality control and medical decision-making, enhancing the overall quality of medical services. By accurately querying and managing blood specimens, this system reduces the medical risks caused by blood specimen confusion, loss, or misuse. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the embodiments of the present invention and constitute a part of this application. The illustrative embodiments and descriptions thereof are used to explain this application and do not constitute an improper limitation of this application. In the drawings: Figure 1 FIG. is a structural diagram of an optional blood specimen storage management system for a blood transfusion department according to an embodiment of the present application; Figure 2 FIG. is a flowchart of an optional method for storing data in a preset medical storage space according to an embodiment of the present application.

[0018] The realization, functional features, and advantages of the objectives of the present invention will be further described in conjunction with the embodiments with reference to the drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0020] As Figure 1 shown, the present application provides a blood specimen storage management system for a blood transfusion department, including: The integrated information collection module 101 is used to obtain the collection data, storage environment data, blood test data, and blood usage dynamic data of the blood specimen set in real time, and generate a radio frequency identification tag code for the blood specimen set; among them, the collection data includes the collection time and the collector information; the storage environment data includes the storage time, storage location, and storage requirements; The blood specimen storage module 102 is used to store the collection data, storage environment data, blood test data, and blood usage dynamic data of the blood specimen set in a preset medical storage space; The blood specimen query module 103 is used to query the storage location of the blood specimen set in the preset medical storage space in real time according to the radio frequency identification tag code of the blood specimen set; The intelligent environment monitoring module 104 is used to monitor the temperature, humidity, and light intensity of the storage location of the blood specimen set; The data analysis and decision support module 105 is used to optimize the storage state of the blood specimen set in the preset medical storage space.

[0021] Based on the embodiments provided in this application, the integrated information collection module obtains the full-process data of blood specimens in real time, including collection data, storage environment data, blood test data, and blood usage dynamic data, and generates a radio frequency identification tag code; this automated data collection and identification process significantly reduces the reliance on paper records, thereby improving the retrieval speed and accuracy of blood specimen information and optimizing the tracking and management efficiency of blood specimens; the intelligent environment monitoring module monitors the temperature, humidity, and light intensity of the storage location in real time to ensure that the blood specimens are always in suitable storage conditions; the blood specimen query module can query the storage location of the blood specimen in real time according to the radio frequency identification tag code, greatly shortening the time to find a specific blood specimen in an emergency; the data analysis and decision support module optimizes the storage state of the blood specimen set, improving the utilization rate of the preset medical storage space; transforming the collection, processing, and storage information of blood specimens from paper records to electronic management facilitates the long-term preservation, rapid retrieval, and sharing of information. This information-based management not only improves work efficiency but also provides data support for medical quality control and medical decision-making, enhancing the overall quality of medical services; by accurately querying and managing blood specimens, this system reduces the medical risks caused by blood specimen confusion, loss, or misuse.

[0022] Optionally, as Figure 2 shown, storing the collection data, storage environment data, blood test data, and blood usage dynamic data of the blood specimen set in a preset medical storage space includes: S201, creating a preset medical storage space; This space can be a physical server cluster or a cloud storage service, depending on the scale and requirements of the medical institution.

[0023] S202, for each blood specimen included in the blood specimen collection, create a data encapsulation unit corresponding to the blood specimen; wherein, each data encapsulation unit includes collection data, storage environment data, blood test data, and blood usage dynamic data; each data encapsulation unit is assigned an identifier for being located in a preset medical storage space. S203, based on the attributes of the collection data, storage environment data, blood test data, and blood usage dynamic data, construct a hierarchical bounding volume tree; wherein, each data encapsulation unit corresponds to a node in the hierarchical bounding volume tree, and the bounding volume of the node includes the data characteristics of the data encapsulation unit. Each attribute can be regarded as a dimension. S204, store each data encapsulation unit in the hierarchical bounding volume tree.

[0024] Further, based on the attributes of the collection data, storage environment data, blood test data, and blood usage dynamic data, construct a hierarchical bounding volume tree; storing each data encapsulation unit in the hierarchical bounding volume tree includes: Determine the weight corresponding to each data encapsulation unit. Create the root node of the hierarchical bounding volume tree, and the bounding volume of the root node includes the logical spatial positions of the collection data, storage environment data, blood test data, and blood usage dynamic data. According to the attributes and weights of the data encapsulation units, allocate the data encapsulation units to the leaf nodes of the hierarchical bounding volume tree. In each node of the hierarchical bounding volume tree, use the key-value pair structure of the B-tree to manage the child nodes of each node.

[0025] Further, in each node included in the hierarchical bounding volume tree, for the non-leaf nodes of the hierarchical bounding volume tree, the key represents the boundary of the bounding volume of the child node, and the value represents a pointer to the child node. For the leaf nodes of the hierarchical bounding volume tree, the key represents the attributes of the data encapsulation unit, and the value represents a pointer to the data encapsulation unit. ; Wherein, is the boundary of the bounding volume of a certain node in the hierarchical bounding volume tree; is the number of data encapsulation units included in the node; is the weight of the th data encapsulation unit; is the is the boundary of the bounding box of the nth data encapsulation unit, where is the number of data encapsulation units; the min function is used to find the minimum value from a set of values; the max function is used to find the maximum value from a set of values.

[0026] Furthermore, optimize the storage status of the blood specimen set in the preset medical storage space, including: Define the optimization objectives for the storage status of the blood specimen set in the preset medical storage space; among them, the optimization objectives include storage layout objectives, access efficiency objectives, environmental adaptability objectives, and data retrieval efficiency objectives; Among them, the storage layout objective: According to the types and characteristics of blood specimens, as well as the requirements of the storage environment, optimize the physical layout of blood specimens in the storage space. The access efficiency objective: Reduce the time and path for accessing blood specimens, especially for blood specimens with urgent needs. The environmental adaptability objective: Ensure that the storage environment matches the preservation requirements of blood specimens to maintain the stability and reliability of blood specimens; the data retrieval efficiency objective: Improve the speed and accuracy of retrieving blood specimens based on blood test data and storage environment data.

[0027] Initialize the population; among them, each individual in the population contains two sets of genes, one set of genes represents the structure of the hierarchical bounding box tree, and the other set of genes represents the structure of the B-tree; Select individuals according to the proportion of the fitness value of the individual in the total fitness for crossover operation and mutation operation; among them, the fitness value is evaluated based on the following indicators: storage layout, storage efficiency, environmental compliance, and storage proximity of data encapsulation units; Among them, storage efficiency: Evaluate the matching degree between the bounding box of nodes in the hierarchical bounding box tree and the actual data characteristics, as well as the uniformity of the distribution of key-value pairs in the B-tree; access speed: Evaluate the response time of the hierarchical bounding box tree and the B-tree structure to query operations, including the average query path length; environmental compliance: Evaluate the matching degree between the storage environment and the requirements of blood specimens; storage proximity of data encapsulation units: Evaluate the physical proximity of relevant blood specimen data in the storage space to reduce the moving distance during access; After the crossover operation and mutation operation are completed, select individuals with fitness higher than the fitness threshold from the final population; among them, the individuals with fitness higher than the fitness threshold are the optimal combination of the hierarchical bounding box tree and the B-tree structure.

[0028] Furthermore, the storage layout is evaluated based on the following formula: ; Among them, represents the score of the storage layout, and the higher its value, the better the storage layout; represents the sum of the bounding box volumes of all nodes in the hierarchical bounding box tree; is the bounding box volume of the th node in the hierarchical bounding box tree; is the total number of nodes in the hierarchical bounding box tree; represents the total capacity of the preset medical storage space; If the ratio of the sum of the bounding box volumes of the nodes in the hierarchical bounding box tree to the volume of the total storage space is smaller, then the unused storage space is less, and thus the efficiency of the storage layout is higher. In this way, it can be ensured that during the optimization process, not only the utilization rate of the storage space is considered, but also the organization method of the storage space is considered to achieve a more efficient storage layout. This efficiency score will be used to evaluate the fitness of each individual in the population, thereby guiding the selection, crossover, and mutation operations of the genetic evolution structure optimization algorithm.

[0029] The storage efficiency is evaluated based on the following formula: ; where, is the access speed score of the B-tree; is the maximum path length for accessing blood specimens; is the average path length for accessing blood specimens; is an adjustment parameter used to control the influence of the path length on the score.

[0030] Furthermore, individuals are selected according to the ratio of the fitness value of the individual to the total fitness for crossover operations and mutation operations, including: Randomly select two parent hierarchical bounding box trees and generate new offspring by exchanging some subtrees or nodes; Randomly select two parent B-trees and generate new offspring by exchanging key-value pairs or subtree structures; Randomly change the bounding box parameters of the nodes or the connection relationships of the nodes; Randomly change the positions of the key-value pairs or modify the splitting strategy or merging strategy of the nodes; Combine the offspring after crossover and mutation with the original population, select the optimal individuals according to the fitness values, and form a new generation of population; repeat the crossover operation and mutation operation based on the new generation of population until there are individuals in the final population with fitness higher than the fitness threshold.

[0031] Furthermore, the blood test data includes the specimen type of the blood, ABO blood type and RhD antigen typing information, blood routine information, coagulation function information, and antibody screening information; the specimen types include venous whole blood specimens, arterial whole blood specimens, capillary whole blood specimens, plasma specimens, and serum specimens; The data analysis and decision support module is also used to analyze the blood test data and storage environment data of the blood specimen set to generate cross-matching reference information for the blood specimen set.

[0032] Furthermore, the blood specimen storage management system for the blood transfusion department further includes: The storage information backup module is used to perform storage backup processing on the collection data, storage environment data, blood test data, and blood usage dynamic data of the blood specimen set to generate backup management information; The user interaction module is wirelessly connected to the blood specimen query module and is used for medical staff to input, query, and update the information of the blood specimens in the blood specimen set through voice or touch screen.

[0033] Furthermore, the user interaction module includes an intelligent environment monitoring and prompting unit. The intelligent environment monitoring and prompting unit is used to display the temperature, humidity, and light intensity of the storage environment of the blood specimens in the blood specimen set, and to display an alarm message when the temperature, humidity, or light intensity of the storage environment of the blood specimens does not meet the requirements of the blood specimen storage environment.

[0034] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied to other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A blood specimen storage and management system for a blood transfusion department, characterized in that: include: An integrated information collection module is used to obtain the collection data, storage environment data, blood test data and blood usage dynamic data of the blood sample set in real time, and generate a wireless radio frequency identification tag code of the blood sample set; wherein the collection data includes the collection time and collector information; the storage environment data includes the storage time, storage location and storage requirements; A blood sample storage module, used for storing the blood sample collection data, storage environment data, blood test data and blood usage dynamic data of the blood sample set in a preset medical storage space; A blood sample query module, used for querying the storage location of the blood sample set in the preset medical storage space in real time according to the wireless radio frequency identification tag code of the blood sample set; An intelligent environment monitoring module, for monitoring the temperature, humidity and light intensity of the storage location of the blood specimen set; The data analysis and decision support module is used to optimize the storage status of the blood specimen set in the preset medical storage space.

2. The blood specimen storage and management system for blood transfusion department according to claim 1, characterized in that: The storing of the blood sample collection data, storage environment data, blood test data and blood usage dynamic data in a preset medical storage space includes: Creating the preset medical storage space; For each blood sample included in the blood sample set, a data encapsulation unit corresponding to the blood sample is created; wherein each data encapsulation unit includes collection data, storage environment data, blood test data, and blood use dynamic data; each data encapsulation unit is assigned an identifier for being located in the preset medical storage space; Based on the attributes of the collected data, the storage environment data, the blood test data and the blood usage dynamic data, a hierarchical bounding box tree is constructed; wherein each data encapsulation unit corresponds to a node in the hierarchical bounding box tree, and the bounding box of the node includes the data features of the data encapsulation unit; Each data encapsulation unit is stored in the hierarchical bounding box tree.

3. The blood specimen storage and management system for blood transfusion department according to claim 2, characterized in that: The method constructs a hierarchical bounding box tree based on the attributes of the collected data, the storage environment data, the blood test data and the blood usage dynamic data; Storing each data encapsulation unit in the hierarchical bounding box tree includes: Determine the weight corresponding to each data encapsulation unit; Creating a root node of the hierarchical bounding box tree, wherein the bounding box of the root node includes the logical spatial positions of the collected data, the storage environment data, the blood test data, and the blood use dynamic data; Allocating the data encapsulation unit to a leaf node of the hierarchical bounding box tree according to the attribute and weight of the data encapsulation unit; In each node of the hierarchical bounding box tree, the child nodes of each node are managed using a key-value pair structure of a B-tree.

4. The blood specimen storage and management system for blood transfusion department according to claim 3, characterized in that: In each node included in the hierarchical bounding box tree, for a non-leaf node of the hierarchical bounding box tree, the key represents the boundary of the bounding box of the child node, and the value represents the pointer to the child node; For a leaf node of the hierarchical bounding box tree, the key represents an attribute of a data encapsulation unit, and the value represents a pointer to the data encapsulation unit; ； in, is the boundary of the bounding box of a node in the hierarchical bounding box tree; is the number of data encapsulation units contained in this node; It is The weight of a data encapsulation unit; It is The weight of a data encapsulation unit; It is The boundary of the bounding box of the data encapsulation unit, is the number of data encapsulation units; the min function is used to find the smallest value from a set of values; the max function is used to find the largest value from a set of values.

5. The blood specimen storage management system for blood transfusion department according to claim 4, characterized in that: The step of optimizing the storage state of the blood specimen set in the preset medical storage space includes: Defining an optimization target for the storage state of the blood specimen set in the preset medical storage space; wherein the optimization target includes a storage layout target, an access efficiency target, an environmental adaptability target, and a data retrieval efficiency target; Initialize a population; wherein each individual in the population contains two groups of genes, one group of genes represents the structure of the hierarchical bounding box tree, and the other group of genes represents the structure of the B-tree; Selecting individuals according to the proportion of their fitness values ​​to the total fitness values ​​to perform crossover and mutation operations; wherein the fitness values ​​are evaluated based on the following indicators: storage layout, storage efficiency, environmental compliance, and storage proximity of data encapsulation units; After the crossover operation and the mutation operation are completed, individuals with fitness higher than a fitness threshold are selected from the final population; wherein the individuals with fitness higher than the fitness threshold are the optimal structural combination of the hierarchical bounding box tree and the B-tree.

6. The blood specimen storage and management system for blood transfusion department according to claim 5, characterized in that: The storage layout is evaluated based on the following formula: ； in, A score representing the storage layout, wherein a higher value represents a better storage layout; Represents the sum of the bounding box volumes of all nodes in the hierarchical bounding box tree; is the first The bounding box volume of each node; is the total number of nodes in the hierarchical bounding box tree; Indicates the total capacity of the preset medical storage space; The storage efficiency is evaluated based on the following formula: ； in, is the access speed score of the B-tree; is the maximum path length for accessing blood specimens; is the average path length for accessing blood specimens; is a tuning parameter that controls the effect of path length on the score.

7. The blood specimen storage and management system for blood transfusion department according to claim 5, characterized in that: The individual is selected according to the proportion of the individual fitness value to the total fitness value to perform the crossover operation and the mutation operation, including: Randomly select two parent hierarchical bounding box trees and generate new offspring by exchanging some subtrees or nodes; Randomly select two parent B-trees and generate new offspring by exchanging key-value pairs or subtree structures; Randomly change the bounding box parameters of the node or the connection relationship of the node; Randomly change the position of key-value pairs or modify the node splitting strategy or merging strategy; Combine the offspring after crossover and mutation with the original population, select the best individuals according to the fitness value, and form a new generation population; repeat the crossover and mutation operations based on the new generation population until there are individuals with fitness higher than the fitness threshold in the final population.

8. The blood specimen storage and management system for blood transfusion department according to claim 1, characterized in that: The blood test data includes blood specimen type, ABO blood type and RhD antigen typing information, blood routine information, coagulation function information and antibody screening information; the specimen types include venous whole blood specimens, arterial whole blood specimens, capillary whole blood specimens, plasma specimens and serum specimens; The data analysis and decision support module is further used to analyze the blood test data and storage environment data of the blood sample set to generate cross-matching reference information of the blood sample set.

9. The blood specimen storage and management system for blood transfusion department according to claim 1, characterized in that: The blood transfusion department blood specimen storage management system also includes: A storage information backup module, used for performing storage backup processing on the collection data, storage environment data, blood test data and blood usage dynamic data of the blood specimen set to generate backup management information; The user interaction module is wirelessly connected to the blood sample query module and is used by medical personnel to input, query and update the information of the blood samples in the blood sample set through voice or touch screen.

10. The blood specimen storage management system for blood transfusion department according to claim 9, characterized in that: The user interaction module includes an intelligent environment monitoring and prompting unit, which is used to display the temperature, humidity and light intensity of the storage environment of the blood samples in the blood sample set, and display an alarm message when the temperature, humidity or light intensity of the storage environment of the blood samples does not meet the storage environment requirements of the blood samples.

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