Sample testing method and laboratory automation system

Abstract

The application relates to a sample detection method and a laboratory automation system, the method is applied to a laboratory automation system, the laboratory automation system provides a man-machine interaction interface; in response to an editing instruction triggered for a target sample on the man-machine interaction interface, a test task corresponding to a detection item of the target sample is generated; the editing instruction comprises a target detection resource specified for the detection item; the detection item is at least one, and the test task corresponding to each detection item is bound to the specified target detection resource; the target sample is scheduled to the bound target detection resource based on the test task, so as to perform detection on the detection item corresponding to the test task. The method realizes customization of a target detection resource, meets sample detection requirements of a complex and refined scene, and can improve sample detection accuracy.

Description

Technical Field

[0001] This application relates to the field of medical laboratory automation technology, and in particular to a sample testing method and a laboratory automation system. Background Technology

[0002] In automated medical testing laboratory systems, there may be multiple instruments with identical functions. Samples are routed to one of these instruments for testing. Taking immunoassay as an example, if the automated system has multiple immunoassay analyzers, then the sample will be routed to one of them for testing.

[0003] In traditional methods, the system dynamically determines which instrument to schedule a sample for experiment based on the real-time load. However, this traditional scheduling logic is too rigid, and can only roughly and generally allocate instruments to samples based on the real-time load. This can easily lead to unsuitable instruments being assigned, and it is particularly unable to handle complex and refined scenarios such as sample quality control review and comparative experiments.

[0004] Therefore, it is necessary to propose a solution that can cope with complex and sophisticated scenarios. Summary of the Invention

[0005] To address the technical problems of traditional methods, this application provides a sample testing method, a laboratory automation system, an electronic device, a computer storage medium, and a computer program product.

[0006] Firstly, a sample detection method is provided for application in a laboratory automation system, which provides a human-computer interaction interface; the method includes: In response to an editing command triggered on a target sample via a human-computer interaction interface, a test task corresponding to the detection items of the target sample is generated; the editing command includes specifying a target detection resource for the detection item; there is at least one detection item, and the test task corresponding to each detection item is bound to the specified target detection resource; The target samples are scheduled to the bound target detection resources based on the test task, so as to perform detection on the detection items corresponding to the test task.

[0007] In a second aspect, a laboratory automation system is provided, the system including a human-machine interface device and a controller for providing a human-machine interface, the controller including a processor and a memory, the memory storing a computer program, the computer program being executed by the processor to implement the steps in the method of the first aspect.

[0008] Thirdly, an electronic device is provided, comprising a memory and a processor, wherein the memory stores a computer program, which, when executed by the processor, implements the steps of the method involved in the first aspect.

[0009] Fourthly, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the steps of the method involved in the first aspect.

[0010] Fifthly, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method involved in the first aspect.

[0011] Among the aforementioned sample testing methods, laboratory automation systems, electronic devices, computer storage media, and computer program products, the laboratory automation system provides a human-computer interaction interface that allows users to edit and specify testing resources for a sample. This allows users to proactively and precisely specify the target testing resources for at least one testing item of the target sample during the sample editing stage, thereby automatically generating test tasks bound to the target testing resources for each testing item. Specifically, in response to editing instructions triggered on the target sample through the human-computer interaction interface, test tasks corresponding to the testing items of the target sample are generated; the editing instructions include specifying target testing resources for the testing items; there are at least one testing item, and the test task corresponding to each testing item is bound to the specified target testing resource. Then, the target sample can be scheduled to the bound target testing resource based on the test task to perform testing on the testing item corresponding to the test task. This effectively achieves customization of target testing resources, meeting the sample testing needs of complex and refined scenarios, and improving sample testing accuracy. Attached Figure Description

[0012] Figure 1 This is a flowchart of a sample detection method in one embodiment; Figure 2A This is a schematic diagram of a human-computer interaction interface in one embodiment; Figure 2B This is a schematic diagram of the sample information display area in one embodiment; Figure 3 This is a schematic diagram of the interface for quickly copying detection project information in one embodiment; Figure 4 This is a schematic diagram of the interface for automatically generating a task box for retesting to be confirmed in one embodiment of the project retesting; Figure 5 This is a schematic diagram of the interface for editing work nodes in one embodiment; Figure 6 This is a schematic diagram of the interface for automatically generating a task box to be confirmed in one embodiment; Figure 7 This is a schematic diagram of the interface for sorting project names in one embodiment; Figure 8 Here is a flowchart of a sample detection method in another embodiment; Figure 9 This is a schematic diagram of a portion of the sample editing interface in single-sample editing mode in one embodiment; Figure 10 This is a schematic diagram of the interface for triggering the batch sample editing mode in one embodiment; Figure 11 This is a schematic diagram of a portion of the sample editing interface in a batch sample editing mode in one embodiment. Detailed Implementation

[0013] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0014] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0015] In the following description, the phrase "some embodiments" refers to a subset of all possible embodiments. It should be noted that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0016] In the following description, the terms "first," "second," etc., are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first," "second," etc., may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0017] In some solutions, additional tests can be performed on the sample. The testing status of the additional sample is determined based on its location, and then, based on the testing status, the additional tests are performed after the additional sample reaches the corresponding aspiration station. In this solution, the aspiration stations (emergency or routine) are universal and are occupied in a "first-in, first-out" order. Clearly, this solution also suffers from the problem pointed out in the background—the indiscriminate allocation of instruments according to the "first-in, first-out" order leads to unsuitable instruments that cannot handle complex and detailed scenarios such as sample quality control review and comparative experiments.

[0018] In view of this, this application proposes a sample detection method. In this method, a laboratory automation system provides a human-computer interaction interface that allows users to specify detection resources for sample editing. During the sample editing stage, users can actively and precisely specify the target detection resources for at least one detection item of the target sample, thereby automatically generating test tasks bound to the target detection resources for each detection item. Furthermore, based on this test task, the target sample can be scheduled to the bound, appropriate target detection resources, thus enabling more precise detection processing for the detection items corresponding to the test task. In other words, the solution of this application achieves customization of target detection resources, meeting the sample detection needs of complex and refined scenarios, and improving sample detection accuracy.

[0019] It should be noted that this application does not limit the specific scenarios in which the sample detection method can be applied. For example, it can be used in routine sample detection scenarios, sample quality control scenarios, or comparison test scenarios. Any scenario requiring sample detection can be processed using the sample detection method described in this application. The sample detection method described in this application will be described in detail below.

[0020] like Figure 1 As shown, in some embodiments, a sample detection method is provided, applied to a laboratory automation system, which provides a human-computer interaction interface. The method specifically includes the following steps: S11, in response to an editing instruction triggered on the target sample in the human-computer interaction interface, generates a test task corresponding to the detection item of the target sample; the editing instruction includes specifying a target detection resource for the detection item; there is at least one detection item, and the test task corresponding to each detection item is bound to the specified target detection resource.

[0021] Here, the target sample refers to the sample to be tested using a specified testing resource. The human-computer interaction interface is the interface used to edit the sample, and can be called the sample editing interface. For example, the system can provide a sample editing function entry point in the result browsing interface or the sample management interface. After triggering this entry point, the interface for editing the sample will be displayed, allowing users to perform editing operations such as specifying testing resources for the sample's testing items.

[0022] It should be noted that, unlike traditional sample editing and management interfaces, the human-computer interaction interface of this application allows for the precise specification of specific target detection resources for detection projects. Furthermore, when editing a specified detection resource, it can trigger the generation of a test task bound to that resource. In other words, this application proposes a unique human-computer interaction interface. Based on the editing operations within this interface, a new test task bound to the specified detection resource can be automatically triggered, thereby achieving refined human intervention and making detection more flexible and accurate.

[0023] Target detection resources refer to the relevant resources specified for a detection project and used to detect target samples. Target detection resources can be a single detection resource or a set of detection resources that meet the requirements. For example, if a user selects "retest on a non-original instrument," and there are currently three online detection instruments in the system, the samples will be scheduled to the other two instruments based on the load.

[0024] For example, the target detection resource includes at least one of the following: detection instrument serial number, reagent kit box number, or reagent kit batch number.

[0025] The instrument serial number identifies the designated instrument, allowing precise control over the testing of the target sample on a specific analytical instrument. The target sample dilution ratio refers to the manually set dilution factor for repeat testing. The kit number or batch number identifies a specific kit or batch of kits used for the target sample, ensuring that the target sample is tested using a specific kit or batch of kits.

[0026] In some embodiments, the target detection resource includes at least two of the following: detection instrument serial number, reagent kit number, or reagent batch number. For example, a specific reagent kit number within the instrument can be specified in addition to the detection instrument serial number.

[0027] In some embodiments, the target detection resource further includes the dilution ratio required when performing at least one detection item on the target sample.

[0028] Detection items refer to target parameters or indicators in a sample that need to be qualitatively or quantitatively analyzed. For example, detection items include, but are not limited to, single analytes (such as ions, metabolites, proteins, nucleic acids, etc.) and combinations of multiple analytes.

[0029] In some examples, the test items can be obtained from the laboratory information system (also referred to as the "LIS system") or added by the user in the human-computer interaction interface. One target sample can correspond to one or more test items.

[0030] Specifically, the laboratory automation system (hereinafter referred to as the "System") includes a human-machine interface device (HMI) providing a user interface. Users can select target samples based on the HMI and input editing instructions for the target samples. These editing instructions specify target detection resources for at least one detection item of the target sample. The target detection resources specified for each detection item can be the same or different. In response to the editing instructions, the System generates test tasks corresponding to each detection item. Each test task corresponding to a detection item is bound to the target detection resource specified for that detection item. There can be one or more selected target samples. It should be understood that editing instructions, in addition to specifying target detection resources for the detection items, may also include other editing operations, such as editing the work nodes in the scheduling strategy of the target samples. The editing process for work nodes will be described in detail later and will not be discussed here.

[0031] For example, users can edit and specify the corresponding target detection resources for the detection items of the target sample obtained from the laboratory information system, or they can add new detection items for the target sample in the human-computer interaction interface and edit and specify the corresponding target detection resources for the newly added detection items.

[0032] In some examples, it is prohibited to modify the specified target detection resources of a detection project that has been bound. This is because a detection project in a bound state may have already issued test tasks or test instructions, but it is impossible to determine whether the test tasks have been completed. If modification of detection resources is allowed, it may cause the results of the execution to be inconsistent with the modified detection resources, resulting in errors.

[0033] In some embodiments, the editing instructions may include target detection resources that the user enters for the detection item, or target detection resources that the user selects for the detection item from the display of detection resources available in the system.

[0034] For example, in the human-computer interaction interface, the various detection resources corresponding to the detection items are empty or pending selection. The user can input or select specific target detection resources. The system can obtain the target detection resources input or selected by the user for the detection items and bind them to the test tasks corresponding to the detection items. It should be noted that the target detection resources are at least a portion of the currently available detection resources in the system.

[0035] In some embodiments, step S11 includes: in response to an editing instruction triggered on a target sample in a human-computer interaction interface, acquiring available detection resources in the system and displaying at least some of the available detection resources in the human-computer interaction interface; determining a target detection resource selected from the displayed available detection resources, generating a test task corresponding to the detection items of the target sample, and binding the detection task to the selected target detection resource.

[0036] The available detection resources in the system refer to the real-time online detection resources. Specifically, the available detection resources include at least one of the following: the serial number of the online detection instrument in the system, the kit number and batch number of the detection kit loaded into the system, and the dilution ratio range supported by the online detection instrument serial number.

[0037] In some examples, the available testing resources displayed are real-time online resources in the system, regardless of the specific testing item. In other words, any testing resource in the system that is online can be considered available and can be displayed in whole or in part on the human-machine interface. For example, assuming that instruments N001-C8 and N002-X8 are online (i.e., connected to the system) and instrument N003-X8 is offline (i.e., not connected to the system), then regardless of the current load status of each instrument or the target testing item the user wants to specify, the instrument serial numbers of the online instruments N001-C8 and N002-X8 will be displayed on the human-machine interface for the user to select, while the instrument serial number of N003-X8 will not be displayed. As another example, when reagent kit numbers SJ001-ANA and SJ002-ANA are both loaded into the system's reagent storage, the human-machine interface displays these two reagent kit numbers based on the real-time reagent loading status.

[0038] In other examples, such as those above, where the editing command includes specifying a target detection resource for a test item on the target sample, the displayed available detection resources are those associated with that test item (i.e., the test item for which the target detection resource needs to be specified). In other words, the displayed available detection resources are those currently online in the system and associated with the test item for which the target detection resource needs to be specified. For example, when editing to specify a target detection resource for the ANA test item on a target sample, the system determines that the ANA test item should be performed by an immunoassay analyzer. Therefore, even though the biochemical analyzer NC001-C8, immunoassay analyzer NC002-X8, and immunoassay analyzer NC003-X8 are all currently online in the system, the human-machine interface will only display the instrument serial numbers NC002-X8 and NC003-X8, which are associated with the ANA test item, for the user to select.

[0039] For ease of understanding, combined with Figure 2A Provide a schematic illustration of the human-computer interaction interface. For example... Figure 2A As shown, after selecting a target sample "AQ1" in the human-computer interaction interface 20, multiple detection items corresponding to the target sample "AQ1" can be displayed in the item editing area 200, such as item 1 to item 3.

[0040] Figure 2A The fields "Instrument," "Reagent Kit Batch Number," and "Reagent Kit Box Number" are used to select the testing instrument, reagent kit batch number, and reagent kit box number, respectively. Taking Project 1 as an example, users can click the drop-down boxes for the "Instrument," "Reagent Kit Batch Number," and "Reagent Kit Box Number" fields in Project 1 to display the corresponding drop-down lists, which include available testing instrument serial numbers, reagent kit batch numbers, and reagent kit box numbers. Users can then select the desired testing instrument serial number, reagent kit batch number, or reagent kit box number. Based on the user's selection, the system can bind at least one of these testing instrument serial number, reagent kit box number, or reagent kit batch number to Project 1. While setting the target testing resource, users can also select the corresponding "Dilution Ratio" according to the actual needs of different projects.

[0041] In some examples, when the user does not need to specify detection resources for the target sample, automatic instrument allocation can be selected for Project 1, and this application does not impose any restrictions. It should be noted that, in addition to displaying the project editing area, the human-computer interface can also be used to display the work editing area (see...). Figure 5 (As shown) and / or the sample information display area. Please refer to... Figure 2A The area marked 210 is the sample information display area. Figure 2B Yes Figure 2A The magnified effect of sample information display area 210 in the image. For example... Figure 2B As shown, the sample information display area can display the sample location (e.g., sample discharge, sample injection, centrifugation, opening, etc.) and the sample cap status (e.g., capped, capless).

[0042] Through the sample information display area, users can clearly understand the status and location of samples, avoid some invalid operations, and accurately capture abnormal samples, reducing the cost of anomaly investigation.

[0043] In some embodiments, the system includes middleware, which refers to a software layer or software system independently deployed between the testing equipment and the laboratory information system. The system provides a human-computer interaction interface specific to this invention through the middleware. After the user inputs editing instructions for the target sample through the human-computer interaction interface, the middleware receives the user's editing instructions and generates a new test task bound to the target testing resource for the corresponding testing item of the target sample. This target testing resource is the testing resource specified in the editing instructions for that testing item. It should be understood that the target testing resource bound to the new test task (i.e., the core attribute of the task) is locked. When it is necessary to obtain relevant test task information for the target sample, relevant information can be obtained based on the sample editing content of the middleware. For example, the middleware can be used to obtain information such as that Project A-Instrument (i.e., the instrument for Project A) is specified as automatically allocated, and Project B-Instrument is specified as N001-C8 (i.e., the instrument for Project B is specified as the specific instrument N001-C8). This ensures that the testing resources are scheduled according to the user's instructions.

[0044] In some embodiments, the system supports full-process manual intervention. It should be understood that the core process of sample detection consists of three stages: before the sample is loaded onto the production line, during the testing tasks after loading, and the completion of the testing tasks on the production line. This three-stage sample detection process is referred to as the full process. Here, "loading" refers to loading onto the production line device. The system allows users to edit samples at any stage of the full process and specify target detection resources for their testing items; therefore, it can be described as: the system supports full-process manual intervention.

[0045] For example, samples that have completed testing on the production line or samples that are currently undergoing testing (i.e., when the sample is in the testing phase after it has been put into production) can be selected by the user as target samples. The user can input editing instructions to edit the specified target detection resources for the detection items of the target sample, thereby achieving manual intervention. Then, the system can convert the user's editing instructions into test tasks with detection resource constraints, that is, the test task corresponding to the detection item is bound to the specified target detection resource.

[0046] It is important to emphasize that in some traditional solutions, some detection tasks and scheduling strategies can be pre-configured before the sample is submitted online. After the sample is submitted or the detection task is started, it must be executed according to the pre-configured detection tasks or scheduling strategies, and the user cannot intervene midway. The solution in this embodiment supports full-process intervention. Users can access the unique human-computer interaction interface of this solution at any time to specify target detection resources for any sample and any detection item of the sample (existing detection items or newly added detection items), which greatly improves flexibility and convenience.

[0047] Furthermore, the sample status does not affect the timing of human intervention. In other words, regardless of the sample's status (e.g., during sample injection, centrifugation, opening the cap, offline interruption, etc.), users can access the unique human-computer interaction interface of this case to edit the specified target detection resources for any detection item of the sample.

[0048] In some embodiments, the system only supports editing samples at specific locations (such as on a track) or in specific states. Editing samples outside of these specific locations or states can easily cause the system to freeze. Therefore, after receiving an editing instruction from the user for the target sample but before responding to it, the system can detect the current location and / or current state of the target sample, and verify whether the target sample is suitable for editing based on the current location and / or current state. If suitable, a test task corresponding to the detection items of the target sample is generated in response to the editing instruction (i.e., step S11 is executed); if unsuitable, the editing operation is rejected, and an error warning is issued.

[0049] S12, based on the test task, schedule the target sample to the bound target detection resource to perform detection on the detection item corresponding to the test task.

[0050] Since test tasks are tied to target detection resources, these resources then act as resource constraints on the test tasks. When planning paths for target samples based on test tasks, these resource constraints must be prioritized. For example, if instrument A is specified for a particular test item of the target sample, the scheduler will force the target sample to be sent to instrument A even if instrument B is idle, or wait while instrument A is busy.

[0051] It should be understood that when an operator has doubts about the historical results of instrument B (e.g., suspecting instrument contamination), they may wish to schedule the target sample to instrument A for comparison testing. However, if the traditional method dynamically allocates instruments based on real-time load, the target sample will still be sent to instrument B when instrument A is busy but instrument B is idle, thus failing to meet the requirements for comparison data. For example, if an operator suspects that ANA kit 1 on instrument A is malfunctioning, they may wish to automatically test the target sample using ANA kit 2. However, if the traditional method dynamically allocates kits based on real-time load, the target sample will automatically be tested using ANA kit 1 when the remaining quantity of ANA kit 1 is low but the remaining quantity of ANA kit 2 is high, again failing to meet the requirements for comparison experiments. Using the solution proposed in this application, the target sample can be scheduled to a more suitable instrument and / or kit number or batch number for testing, unaffected by load interference.

[0052] In some examples, when only the reagent kit number or batch number is specified for the resource, the system will schedule the samples according to the real-time loading location of the reagent kit, regardless of which testing instrument the reagent kit is actually loaded onto during the sample scheduling process.

[0053] In the above method, the laboratory automation system provides a human-computer interaction interface that allows users to specify testing resources for sample editing. This enables users to proactively and precisely specify the target testing resources for at least one testing item of the target sample during the sample editing stage, thereby automatically generating test tasks bound to the target testing resources for each testing item. Then, the target sample can be scheduled to the bound target testing resources based on the test task to perform the corresponding testing item. In other words, this achieves customization of target testing resources, enables fine-grained control during the sample testing process, and meets the sample testing needs of complex and sophisticated scenarios.

[0054] Furthermore, users do not need to remove samples from the pipeline for offline processing, nor do they need to perform complex operations on the instrument itself. All user-specified / editing operations are completed within the unified middleware interface, enabling online, real-time, and refined management of online samples, improving operational efficiency and enhancing the user experience. Overall, the above solution ensures the automated and efficient operation of the main pipeline while creating a "green channel" for special scenarios requiring manual intervention, resolving the conflict between the needs of scientific research, strict quality control, and re-inspection / machine replacement and fully automated scheduling.

[0055] In some embodiments, the human-computer interaction interface displays at least one detection item for editing the target sample and a specified target detection resource; the at least one detection item includes a detection item that has been detected, which can be referred to as the first detection item.

[0056] Among them, the test items that have been completed refer to the test items that have been tested and obtained experimental results. It should be understood that both the test items that were successfully tested and those that failed have completed the test and obtained the corresponding experimental results, and therefore, they all belong to the test items that have been completed.

[0057] In this embodiment, the first detection item that has completed the detection has a corresponding copy control. The system can generate a new test task for the first detection item in response to triggering the copy control; wherein the new test task carries at least a portion of the original detection resources corresponding to the first detection item; the original detection resources refer to the target detection resources corresponding to the first detection item in the completed detection.

[0058] Specifically, in response to the triggering of the copy control for the first test item, new test item information corresponding to the first test item is generated for user confirmation; the user can edit the new test item information and trigger a confirmation operation on the finally confirmed test item information; in response to the confirmation operation triggered by the user, a new test task for the first test item is generated based on the finally confirmed test item information.

[0059] Please see Figure 3 In the human-computer interaction interface 30, the two detection items within the dashed box 310 are both first detection items that have been completed. Each of the two first detection items has a corresponding copy control "+". Taking item 1 as an example, triggering its corresponding copy control 320 automatically creates a new detection item information 330 for item 1. The detection resources within the detection item information 330 (such as dilution ratio, instrument / reagent batch number / reagent box number, etc.) can fill at least part of the original detection resources. The original detection resources refer to the target detection resources corresponding to item 1 in the completed detection. For example... Figure 3 As shown, the newly created test item information 330 has a task box to be confirmed. For example, there is a task box to be confirmed under the "Dilution Ratio" field; there is a task box to be confirmed under the "Instrument" field. The task box to be confirmed is filled with "Retest with original instrument", which means that the original instrument resources have been configured.

[0060] Users can edit the newly created test item information 330, and confirm the edited test item information or the original test item information 330. In response to the user's confirmation operation, a new test task (i.e., a new test task) is generated for item 1 based on the finally confirmed test item information.

[0061] It should be understood that if a new test task carries all the original testing resources corresponding to the first testing item, rapid retesting can be achieved; if a new test task carries some testing resources, rapid comparative experiments can be achieved.

[0062] In the above solution, by setting a copy control for the completed test items, new test tasks can be quickly generated, thereby enabling more convenient sample testing, such as convenient retesting and comparison experiments.

[0063] In some embodiments, if there is at least one second detection item that failed to be detected in the target sample, a corresponding retest task box to be confirmed is generated for each second detection item in the human-computer interaction interface.

[0064] Specifically, the system can automatically monitor the test results (i.e., experimental results) for completed test items. Test items with a "failure" result can be recorded as second test items. It should be understood that second test items are included within the first test items that have been completed. For each second test item, a "To be Confirmed Retest Task Box" can be automatically generated in the project editing area of ​​the human-computer interaction interface. This "To be Confirmed Retest Task Box" is used to generate test tasks for retesting the second test item. It should be understood that the "To be Confirmed Retest Task Box" is filled with test resources for the second test item, and the retest test task is bound to the test resources filled in the "To be Confirmed Retest Task Box".

[0065] In the above scheme, for items in the target sample that failed detection, automatically generating a retest task box to be confirmed in the human-computer interaction interface can effectively improve the processing efficiency of the retest task.

[0066] In some examples, the pending retest task box is configured to automatically populate the target detection resource corresponding to the second detection item when the detection fails; In other examples, the pending retest task box is configured to automatically populate at least one detection resource that is different from the target detection resource corresponding to the failure of the second detection item.

[0067] For example, a user can edit the detection resources filled in the retest task box to be confirmed, and confirm the edited retest task box or the original retest task box to be confirmed. In response to the user's confirmation operation, a test task for retesting the second detection item is generated based on the finally confirmed retest task box, which can be simply referred to as a "retest task". The retest task is bound to the target detection resources in the finally confirmed retest task box.

[0068] Please see Figure 4 The test result for Project 2 is "failure". A "Pending Retest" task box for Project 2 is automatically generated in the project editing area of ​​the human-computer interaction interface. Figure 4As shown, the dashed box 410 contains four retest task boxes for confirmation: the "Dilution Ratio" field, the "Instrument" field, the "Reagent Kit Batch Number" field, and the "Reagent Kit Box Number" field. In at least some of these retest task boxes, the target detection resource used when item 2 fails can be automatically filled in. For example, filling the "Retest with Original Instrument" box under the "Instrument" field indicates that the instrument used when the test fails has been configured. Alternatively, it could automatically fill in "Retest with Non-Original Instrument," which is capable of performing the test. Users can edit the resource information filled in the retest task boxes for confirmation. The detection resources in the final confirmed retest task boxes are equivalent to the target detection resources specified by the user, thereby generating a retest task for item 2. This retest task is bound to the target detection resource. The retest task boxes for confirmation effectively improve the processing efficiency of retest tasks.

[0069] In some embodiments, the target sample has a corresponding scheduling strategy; the scheduling strategy includes at least one working node. It should be noted that the working node in the embodiments of this application is essentially a step or process node in the sample detection process. Exemplarily, the working node includes at least one of the following: sample injection, pretreatment, centrifugation, visual inspection, opening the cap, adding sample, rewarming, and mixing.

[0070] The scheduling strategy corresponds to the sample flow path. Typically, one sample corresponds to one sampling node, but multiple sampling nodes can be used if necessary. One or more detection items can be executed in a single sampling node.

[0071] When a detection task corresponding to a detection item for a target sample is obtained, the system automatically generates a scheduling strategy for the target sample. The scheduling strategy must include at least a sample loading node. Based on the scheduling strategy and the detection task, the target sample can be scheduled to the bound target detection resource for detection.

[0072] In some embodiments, when there is at least one failed second detection item in the target sample, both detection resources and working nodes can be configured for the second detection item. Specifically, the system can generate a corresponding retest task box to be confirmed for each second detection item in the human-computer interaction interface, and automatically generate a corresponding working task box to be confirmed in the human-computer interaction interface based on the current cap status of the target sample; responding to the user's confirmation operation of the retest task box to be confirmed and the working task box to be confirmed, the system generates a test task (i.e., a retest task) to retest the second detection item, and generates a scheduling strategy to implement the retest.

[0073] The above solution simplifies the retesting process and is suitable for scenarios involving retesting failed samples.

[0074] In some embodiments, users can modify the scheduling strategy. Specifically, the edit command triggered on the target sample is also used to indicate the work nodes to be changed for the target sample, including newly added work nodes and / or work nodes to be deleted. The system can update the scheduling strategy of the target sample according to the work nodes to be changed; and control the execution path of the target sample based on the updated scheduling strategy. That is, users can flexibly add and delete work nodes in the scheduling strategy, thus enabling users to flexibly and conveniently optimize sample processing nodes for new testing needs. For example, when it is necessary to retest the target sample, there may be a long time since the last detection result. Users can flexibly add centrifugation nodes through edit commands to ensure the stratification effect of the target sample, so that the stratification effect will not affect the final detection result of the target sample during retesting. As another example, when it is necessary to retest the target sample, the sample preprocessing step has already been completed in the previous detection. Executing the sample preprocessing step again will introduce new variables. Users can delete the "preprocessing" work node according to the actual situation.

[0075] Specifically, after receiving the editing instruction, the middleware responds to the editing instruction by changing the work nodes in the scheduling strategy corresponding to the target sample. For example, it adds the indicated new work node and deletes the indicated work node to be deleted, thereby realizing the custom change of work nodes and flexibly updating the scheduling strategy according to the needs.

[0076] For example, if the original scheduling strategy A for a sample is: sample injection, centrifugation, and cap opening, and the user adds a "vision" task through the human-computer interaction interface, then the sample will correspond to the updated scheduling strategy A. ud Sample injection, centrifugation, visual inspection, and cap opening. Subsequent actions can be based on the updated scheduling strategy A. ud This controls the execution path of the target sample.

[0077] In some embodiments, the system supports changes (i.e., additions / deletions) to work nodes at the individual work node level. Specifically, users can edit individual work nodes in the human-computer interaction interface, and the system responds to the user's editing commands by changing the indicated work nodes.

[0078] In some embodiments, the system can also support batch changes of work nodes at the workgroup level. Specifically, a preset workgroup selection area can be displayed in the human-computer interaction interface, where users can select a preset workgroup and trigger an add operation. The system responds to the user-triggered add operation and adds the selected preset workgroup to the target sample. It should be understood that a preset workgroup is a complete set of work nodes, allowing users to add work nodes more conveniently and quickly, i.e., to achieve batch addition of a series of work nodes.

[0079] To facilitate understanding, the following example illustrates the addition of work nodes at the workgroup level. Suppose a commonly used sample has already undergone all previous processing and is stored in a location (such as a cryogenic storage area). In this case, if a user wants to schedule this sample for a new series of processing, the system can support setting work nodes for the sample to form a new scheduling strategy. Subsequently, the sample can be scheduled for a new series of processing using this new scheduling strategy. The inventors of this invention have optimized the system functionality by pre-setting some preset workgroups. Therefore, when a user needs to set new work nodes for a target sample, they can select the desired preset workgroup, quickly setting the entire set of work nodes without having to add them one by one. This allows for faster addition of work nodes, reduces user operating costs, and avoids unnecessary resource consumption caused by the system constantly responding to add operations one by one.

[0080] The above example only illustrates the case of adding work nodes at the workgroup level and does not constitute a limitation. Users can add work nodes at the workgroup level in any situation according to their needs.

[0081] It should be noted that preset workgroups can also be used for batch deletion of work nodes. For example, if a target sample has already been configured with a large number of work nodes, deleting them one by one would be cumbersome and inefficient. In this case, the selected preset workgroup includes at least a portion of the work nodes that can be deleted from the target sample (such as those that have not been executed or analyzed).

[0082] It should be understood that the system supports both individual worker node changes and batch worker node changes at the workgroup level. In other words, the system supports both methods of node change, and users can choose to use a specific method based on their actual needs, or combine the two methods; there are no restrictions on this.

[0083] Please see Figure 5 When work node editing is required, a work editing area 500 is displayed on the human-computer interaction interface. Work nodes can be added and deleted in the work editing area 500. Addable and deleteable work nodes include visual, centrifugal, open cap, sample addition, capping, rewarming, and mixing. For example, the user can trigger the "Add Work" control in the operation control area to add a blank work task box 510. Triggering the drop-down menu in work task box 510 displays a set of selectable work nodes, from which the user can select the desired work node. Additionally, the user can trigger the delete control 520 to delete a work node.

[0084] For example, users can delete not only newly added worker nodes but also worker nodes that were not executed in the original scheduling policy. Once a worker node has been completed, it cannot be deleted. Figure 5 The corresponding delete control is not displayed for "visual" work nodes that are in the "completed" state.

[0085] Please continue reading. Figure 5 The work editing area 500 also displays a preset work group selection area 530. Users can click the drop-down box to display a set of preset work groups to choose from, and select the desired preset work group to quickly configure a set of work nodes for the target sample "AQ1".

[0086] In some embodiments, after receiving an editing instruction for a working node to be changed for a target sample, the system can also automatically generate a task box to be confirmed in the human-computer interaction interface based on the current cap status of the target sample; wherein, the task box to be confirmed includes a sample addition node, and an opening node generated when the cap status is capped. It should be understood that if the current cap status of the target sample is capless, the task box to be confirmed may only include a sample addition node; if the current cap status of the target sample is capped, the task box to be confirmed includes both an opening node and a sample addition node.

[0087] Furthermore, the scheduling strategy of the target sample can be updated based on the confirmed work nodes in the task box to be confirmed and the work nodes to be changed indicated by the editing command. For example, the user can edit the work nodes filled in the task box to be confirmed, confirm the edited work nodes in the task box to be confirmed, or directly confirm the automatically generated work nodes in the task box to be confirmed. Therefore, the confirmed work nodes in the task box to be confirmed can include the edited work nodes or the automatically generated work nodes.

[0088] Please see Figure 6 Taking the current cap status of the target sample as an example, in the work editing area 600 of the human-computer interaction interface, two work task boxes to be confirmed can be generated as shown in box 610. The sample addition node and cap opening node are automatically filled in respectively. The two can be used to assist in updating the scheduling strategy and save user operation costs.

[0089] Compared to the traditional method that can only schedule samples during loading and then schedule them to available testing resources based on their availability after the samples have completed "pre-processing" and reached the testing stage, this embodiment allows users to request that samples be scheduled to a designated target testing resource at any time. It also verifies the critical "opening" step in the scheduling process to ensure that samples can be successfully scheduled to the target testing resource and complete the corresponding testing tasks.

[0090] It should be noted that in this embodiment, the user can input editing instructions for the target sample at any stage of the entire process to add detection tasks (such as regular detection tasks or retest detection tasks). Therefore, when the user inputs editing instructions, they may not know the exact position of the sample on the online body, and thus cannot know whether the sample is capped or not. Therefore, the user may not necessarily add a "cap opening" node when editing the working node. Therefore, the system can automatically detect the current cap status of the target sample to dynamically verify whether to automatically generate a "cap opening" node, ensuring that the sample can be successfully scheduled to the target detection resources and complete the corresponding test tasks.

[0091] In some embodiments, the edit instruction is used to indicate the second working node to be added for the target sample. If the edit instruction is received during the execution of the first working node, the updated scheduling policy is analyzed after the first working node has been completed; if the currently to-be-executed working node in the updated scheduling policy is the newly added second working node, the execution of the second working node is triggered.

[0092] For example, the original scheduling strategy A for the sample is: sample injection, centrifugation, and cap opening. During the execution of the "centrifugation" work node, if an edit command to add a "vision" work node is received from the user via the human-computer interaction interface, the updated scheduling strategy A will be analyzed after centrifugation is completed. ud Sample injection, centrifugation, vision, cap opening. The middleware will handle the incomplete scheduling strategy A. ud The scheduling strategy A is issued to the production line units, which then execute the scheduling strategy sequentially. ud The remaining working nodes (i.e., the vision and lid opening working nodes) are scheduled under strategy A. ud When the currently pending work node is the newly added "Vision" work node, then the "Vision" work node will be triggered to perform visual processing on the target sample.

[0093] In this embodiment, adding a new working node does not interrupt the execution process of the current working node, thus ensuring the accuracy of scheduling.

[0094] In some embodiments, the worker node to be changed includes at least one newly added worker node. In this embodiment, the system sets up a worker node deduplication mechanism to prevent the newly added worker node from being duplicated with a corresponding historical worker node that already exists in the scheduling policy before the update. Specifically, updating the scheduling policy of the target sample according to the worker node to be changed includes: traversing at least one newly added worker node; if the currently traversed newly added worker node has a corresponding historical worker node in the scheduling policy of the target sample that is in an unexecuted state (i.e., unanalyzed state), then one of the newly added worker node and the corresponding historical worker node is retained in the scheduling policy; or, the newly added worker node and the corresponding historical worker node are retained in the scheduling policy, but one of the newly added worker node and the historical worker node is in a shelved state, and the worker node in the shelved state will not be actually executed.

[0095] For example, suppose the new node is a "centrifugal" node, but a "centrifugal" node already exists in the scheduling strategy. Then, two "centrifugal" nodes can be retained in the scheduling strategy, and two duplicate "centrifugal" nodes can also be displayed in the interface. However, one of the "centrifugal" nodes is in a shelved state. When performing sample scheduling, the "centrifugal" node in the shelved state will not be actually executed, thereby avoiding the repeated execution of "centrifugal" processing.

[0096] For example, when a save operation is received for a worker node, it can be triggered to traverse each newly added worker node to compare each newly added worker node with each historical worker node in the unexecuted state (i.e. unanalyzed state) in the scheduling policy before the update of the target sample.

[0097] The deduplication mechanism for work nodes is illustrated below, taking into account situations a and b.

[0098] Scenario a: When processing batch samples, users uniformly edit and add centrifugation nodes, but some samples already have centrifugation nodes. Based on the deduplication mechanism of this working node, for samples with existing centrifugation nodes, the centrifugation nodes will not be updated to their corresponding scheduling strategy, or the historical centrifugation nodes in the scheduling strategy will be replaced with newly added centrifugation nodes. For samples without centrifugation nodes, the centrifugation nodes will be updated to their corresponding scheduling strategy.

[0099] Scenario b: When adding detection items to a target sample, it is generally recommended that users directly add two new working nodes: "Add Sample" and "Open Cap". Before updating these two working nodes to the scheduling strategy corresponding to the target sample, the scheduling strategy for the target sample can be deduplicated to determine whether these two nodes already exist in the previous scheduling strategy and whether they are in an inactive state. If so, deduplication can be performed.

[0100] In this embodiment, the system automatically deduplicates worker nodes and only updates valid worker nodes to the scheduling policy. This avoids the storage resource consumption caused by invalid storage of duplicate nodes, as well as the processing resource consumption caused by repeated execution of duplicate nodes, and also reduces the difficulty of use for users.

[0101] In some embodiments, the updated scheduling policy includes adding new worker nodes; based on the updated scheduling policy, controlling the execution path of the target sample includes: when the target sample is to be executed by adding a new worker node based on the updated scheduling policy, determining whether the new worker node conflicts with the current state of the target sample; the current state includes the cap state and / or the execution state of the worker node; if there is a conflict, the new worker node to be executed is skipped, and the subsequent worker nodes in the scheduling policy are continued to be executed.

[0102] In this embodiment, the system sets up a conflict verification mechanism during execution. This mechanism is used to perform conflict verification when executing the scheduling strategy for the target sample, so as to prevent conflicts between the completed work nodes and the newly added work nodes.

[0103] Specifically, when controlling the execution of new worker nodes for the target sample based on the updated scheduling strategy, the current state of the target sample is obtained, including the cap state and / or the execution state of the worker nodes. Then, based on the current state of the target sample, conflicting new worker nodes are shelved; that is, conflicting new worker nodes are skipped, and subsequent worker nodes in the scheduling strategy are continued to be executed. New worker nodes that do not conflict can be executed normally.

[0104] The cap status indicates whether the target sample has a cap or not. The worker node execution status indicates whether the worker node for the current target sample has been completed.

[0105] Conflicting work nodes refer to work nodes that are unsuitable or should not be executed under the current state of the target sample.

[0106] To facilitate understanding of the conflict checking mechanism during execution, an example is provided below.

[0107] For example, if the target sample is currently in the capless state (i.e., in the opened state), and the user adds a centrifugation node, the centrifugation process will be skipped because the capless sample cannot be centrifuged.

[0108] For example, the target sample has already been sampled, and the user has added a sample addition node. However, if no unexecuted detection items are detected for the sample, it means that sample addition is not required. Therefore, the newly added sample addition node is shelved, and the sample addition process is skipped.

[0109] For example, if the current cap status of the sample is uncapped, and the user adds a cap-opening node, since the current cap is uncapped, there is no need to open it. Therefore, the newly added cap-opening node is put on hold, and the cap-opening process is skipped.

[0110] For example, a pre-set execution order for worker nodes is provided. When the sample executes the current worker node, based on this pre-set order, the user is not allowed to effectively add a worker node that should execute before the current one. For instance, even if a user adds a worker node that should execute before the current one, they can delete or postpone the conflicting new worker node; a postponed worker node will not be actually executed. In other examples, the conflict logic can take other forms, which are not limited here.

[0111] The conflict checking mechanism during execution will be explained below with reference to Table 1.

[0112] Table 1 In Table 1, the work nodes marked "Added"—Visual, Mixing, and Opening—are user-edited new work nodes. It should be noted that in Table 1, the "Completed" status means that the processing corresponding to the work node has been completed, and the upper layer has received the returned execution result. The "Analyzed" status means that the execution instruction or command corresponding to the work node has been issued, instructing the upper layer to execute the processing corresponding to the work node, but the upper layer has not yet received the returned execution result. The "Unanalyzed" status means that the work node has not been executed, that is, the execution instruction or command corresponding to the work node has not yet been issued.

[0113] It should be understood that if a user adds a duplicate work node that already exists in the scheduling strategy for the target sample and is not analyzed (i.e., not executed), the system will perform deduplication based on the work node deduplication mechanism, preventing the user's new work node from being updated in the target sample's scheduling strategy. However, in some cases, simply setting a deduplication mechanism may still lead to conflicts in the execution of some nodes. For example, if the target sample is already in the sampling stage or has already completed sampling, adding a "visual" work node would be meaningless. In this case, the system can determine that the newly added "visual" work node is in a conflict state based on the preset work node execution order, and therefore the newly added conflicting "visual" work node can be deleted or shelved.

[0114] In the above scheme, the conflict verification mechanism based on execution can avoid resource waste caused by repeated operations and prevent the execution failure of conflict nodes (such as the error caused by centrifugation when the sample is uncovered), thereby improving the success rate of the task.

[0115] In some embodiments, there are multiple target samples; multiple target samples can be edited using either a single-sample editing mode or a batch-sample editing mode. Single-sample editing mode refers to editing each target sample individually. Batch-sample editing mode refers to editing multiple target samples in batches.

[0116] In batch sample editing mode, virtual samples are created for multiple target samples to uniformly receive editing instructions; the editing instructions triggered for the virtual samples are batch editing instructions; a mapping relationship is established between the virtual samples and the multiple target samples to be processed in batches; the batch editing instructions triggered for the virtual samples are synchronously mapped to each target sample associated with the virtual samples.

[0117] In other words, the system can more conveniently and efficiently process samples in batches by spontaneously constructing virtual samples.

[0118] Specifically, a virtual sample can be constructed as a "master node" (also called a virtual master node), and associated with multiple target samples (e.g., three target samples) that need to be batch-edited. For example, a mapping relationship can be established between the GUID (Globally Unique Identifier) ​​of the virtual sample and the GUIDs corresponding to the multiple target samples to be batch-processed. User editing commands can be uniformly applied to the virtual sample. Then, in response to batch editing commands input to the virtual sample, the system synchronously maps the batch editing commands input to the virtual sample to each target sample associated with that virtual sample based on the established mapping relationship. For example, if a user edits detection items and / or working nodes for a virtual sample, the system can synchronously edit the corresponding detection items and / or working nodes for each target sample associated with that virtual sample in the background.

[0119] In the above solution, users can achieve batch editing of all associated target samples by only editing virtual samples. This simplifies the batch editing process, avoids the problem of easy omissions when manually editing and configuring each sample one by one, and improves editing efficiency.

[0120] For example, if a deletion instruction for a virtual sample is received, multiple target samples associated with the virtual sample are simultaneously deleted based on the established mapping relationship. This ensures operational traceability (deleting the master node deletes the association) and allows for rapid sample deletion, avoiding invalid tasks due to sample residue.

[0121] In some embodiments, in response to an editing instruction triggered on a target sample in a human-computer interaction interface, generating a test task corresponding to a detection item of the target sample includes: in response to a batch editing instruction triggered on the virtual sample, determining whether a first target sample exists among a plurality of target samples associated with the virtual sample; wherein the first target sample already has an unexecuted first detection task corresponding to a detection item specified by the batch editing instruction; target samples other than the first target sample among the plurality of target samples are second target samples; if so, for each first target sample, synchronously mapping the batch editing instruction to the first target sample to generate a second test task corresponding to the specified detection item of the first target sample, and deduplicating the second detection task and the first detection task, or not synchronously mapping the batch editing instruction to the first target sample; for each second target sample, synchronously mapping the batch editing instruction to the second target sample to generate a test task corresponding to the specified detection item of the second target sample.

[0122] It should be understood that since the batch editing command in this case is fully inputtable, when the batch editing command is triggered for the virtual samples associated with the batch target samples, some target samples may already have unexecuted detection tasks corresponding to the detection items specified by the batch editing command. Therefore, this embodiment can perform intelligent detection judgment and deduplicate the detection tasks corresponding to the same target sample when adding new detection tasks for batch samples, thereby avoiding unnecessary resource consumption caused by repeatedly executing detection tasks.

[0123] In some embodiments, step S12 includes: when executing the sampling node in the scheduling strategy of the target sample, scheduling the target sample to the target detection resource based on the test task, and performing sampling processing to perform detection on the detection item corresponding to the test task.

[0124] It should be understood that the system supports manual intervention at any stage of the sample testing process (i.e., supports full-process manual intervention). Therefore, the test tasks corresponding to the test items can be generated at any stage of the sample testing process. The testing processing performed on the corresponding test items may differ depending on the stage at which the test tasks are generated.

[0125] In some embodiments, the project editing area supports sorting by project name, allowing multiple sets of detection resources corresponding to the same detection project to be displayed together. For example... Figure 7 As shown in 710, sorting by project name allows for the centralized display of the two different sets of testing resources corresponding to Project 1. This enables users to more conveniently and intuitively understand multiple sets of experimental data for the same testing project.

[0126] The sample detection method in this application can be applied in various scenarios, including but not limited to retesting scenarios, comparative experiment management scenarios, and batch sample processing scenarios. These three scenarios will be described in detail below.

[0127] Scenario 1: Retest Scenario In the retest scenario, specific steps 1.1 to 1.4 can be executed: 1.1: When the system detects that the detection result of a certain detection item B of the target sample S is abnormal, the user can start the human-computer interaction interface for editing the target sample S through the result management interface (also known as the sample editing interface corresponding to the target sample S).

[0128] 1.2: Users can select specific instruments and reagent kits as target detection resources for the detection item B based on this human-computer interaction interface.

[0129] 1.3: The system responds to user operations and generates a retest task (i.e., a test task for retesting) that is bound to the target detection resources for detection item B.

[0130] 1.4: The system can execute this retest task to forcibly schedule the target sample S to the specified target detection resource in order to perform detection on the detection item B.

[0131] The solution proposed in this application allows users to actively specify another instrument or another reagent kit to retest the sample during retesting, in order to avoid possible instrument system / reagent errors. This is something that conventional automatic retesting logic (which allocates retesting in real time according to the idle or busy status of the instrument) cannot achieve.

[0132] Scenario 2: Comparative Experiment Management Scenario In the scenario of comparative experiment management, users need to conduct comparative experiments of multiple reagent kits for the same detection item of target sample S. Specifically, steps 2.1 to 2.4 can be executed: 2.1: For the same test item B, the user configures different test resources for test item B based on the human-computer interaction interface.

[0133] 2.2: The system generates multiple test tasks (i.e., comparison test tasks) based on different detection resources configured for detection item B.

[0134] For the same detection item B, each set of detection resources is used to generate one test task, while different sets of detection resources are used to generate multiple different test tasks. Each test task is bound to a corresponding set of detection resources (i.e., target detection resources).

[0135] 2.3: The system can execute each test task to forcibly schedule the target sample S to the corresponding detection resource (i.e., the target detection resource) to perform detection on the detection item B.

[0136] For example, different reagent kits can be used on the testing instrument to perform comparative tests on the target sample S for test item B, thus meeting the needs of doctors to conduct comparative experiments on the instrument using different reagent kits.

[0137] The scheme proposed in this application ensures that the samples in the comparative experiment are executed accurately under the specified comparative detection resources, thus guaranteeing the comparability of the data.

[0138] 2.4: The system can compare the detection results of each test task for detection item B separately to obtain the comparison results using different detection resources.

[0139] Scenario 3: Batch Sample Processing In batch sample processing scenarios, users need to perform batch detection of item B on multiple target samples S. Specifically, steps 3.1 to 3.4 can be executed: 3.1: The user selects multiple target samples S that need to be edited.

[0140] 3.2: Users can edit and configure unified target detection resources (i.e., unified resource constraints) for multiple target samples S based on the human-computer interaction interface for the detection item B.

[0141] 3.3: The system generates batch detection tasks based on the target detection resources configured in the edit settings.

[0142] 3.4: The system forces each target sample S to the corresponding target detection resource based on the batch detection task to perform detection on the detection item B.

[0143] For example, if multiple samples show abnormal CRP results in the test results of the day, but this abnormal result is not conducive to doctors further determining whether the patient has a bacterial or viral infection, then PCT testing can be added to this batch of samples.

[0144] The solution proposed in this application can meet the sample analysis needs of various clinical testing scenarios.

[0145] It should be understood that the solution proposed in this application can also be applied to quality control scenarios. In traditional quality control processes, when the quality control of a specific reagent kit fails, the system cannot specify another normal reagent kit to retest the quality control sample in order to pinpoint whether the problem is systemic or caused solely by that particular reagent kit. With the solution proposed in this application, users can flexibly specify another reagent kit to retest the quality control sample to further determine the cause. The system can automatically generate multiple specific test tasks bound to different testing resources to meet the quality control compliance requirements of different laboratories.

[0146] like Figure 8As shown, in another embodiment, taking the scenario of adding a second detection item when the detection result of the first detection item is abnormal as an example, the sample detection method is illustrated. The method specifically includes the following steps: S801, Obtain the test results of the sample under the first test item.

[0147] For example, the first test item could be a CRP test item. For instance, if multiple samples show abnormal CRP results in the test results for the day, but these abnormal results are not helpful for doctors to further determine whether the patient has a bacterial or viral infection, the method in this embodiment can be used to allow users to add other tests (i.e., second tests, such as PCT tests) to this batch of samples, thereby performing advanced testing on this batch of samples.

[0148] S802, determine if the test result is abnormal. If yes, proceed to S803; otherwise, proceed with the subsequent processing in the normal test procedure.

[0149] S803, in response to user operation, launches the sample editing interface.

[0150] The sample editing interface is the human-computer interaction interface mentioned above.

[0151] For example, during the process of launching the sample editing interface, in addition to initializing the content of the visual interface, resource configuration preparation can also be performed in the background, such as obtaining available detection resources in the system (e.g., the box number and batch number of the detection instrument and reagent kit), and preparing a confirmation retest task box for failed sample retests, so as to facilitate the configuration of target detection resources for subsequent detection items.

[0152] S804 displays each sample that has detected anomalies in the sample editing interface.

[0153] S805, determine the target sample to be detected and the target editing mode.

[0154] The target sample to be tested is selected from the displayed samples and determined as the sample to be tested.

[0155] If the target editing mode is single-sample editing mode, then editing is performed on a single target sample, and S806 can be executed; if the target editing mode is batch-sample editing mode, then batch-editing is performed on multiple target samples, and S810 can be executed.

[0156] It should be understood that different editing modes use different interface view models, and the interface layout or content in the sample editing interface may differ.

[0157] S806, in the sample editing interface, displays the project editing area for a single target sample in single sample editing mode.

[0158] Please see Figure 2A This demonstrates the project editing area 200 for a single target sample (sample number: AQ1) in single-sample editing mode, where the corresponding editable detection items can be displayed.

[0159] In some examples, the sample editing interface in single-sample editing mode can also display a working editing area. For example... Figure 9 As shown, in single-sample editing mode, the sample information of a single target sample highlighted in 910 can be displayed, and the corresponding editable work node can be displayed in the work editing area 920. Figure 9 The two "visual" working nodes highlighted in section 930 are the original working nodes before the user edits them. That is, in some examples, the original working node of the target sample before the user edits it can be displayed in the corresponding working editing area.

[0160] S807, in response to the user's project selection operation, displays the second detection item that needs to be detected for a single target sample in the project editing area, and displays the available detection resources corresponding to the second detection item.

[0161] Please see Figure 2A The project editing area 200 displays a list of test items, from which users can select the second test item to be tested.

[0162] For example, a retest task box can be automatically generated in the project editing area for failed test items, allowing users to select retesting options. Figure 4 As shown in 410.

[0163] S808, determine the target detection resource selected by the user for the second detection item for a single target sample.

[0164] The target detection resources are selected from the available detection resources. Specifically, all available detection resources in the system (such as available detection instruments and reagent kits) can be obtained and presented to the user for selection when the user performs a resource selection operation.

[0165] S809, generate the detection task corresponding to the second detection item, and bind the detection task to the target detection resource.

[0166] S810 displays the project editing area in the batch sample editing mode within the sample editing interface.

[0167] Please see Figures 10 to 11 ,like Figure 10As shown, users can select the three samples highlighted in box 1001 as target samples, and then trigger the "Sample Editing" control 1002 to enter the batch sample editing mode. It should be understood that the project editing area in the batch sample editing mode is blank, that is, the detection items registered for each of the three target samples will not be displayed. Only the detection items newly added for the unified batch processing of the three target samples will be displayed.

[0168] Figure 11 This is used to illustrate the sample display area of ​​the sample editing interface in batch sample editing mode. It should be understood that in batch sample editing mode, because virtual samples are constructed, it is not necessary to perform individual editing operations on each target sample; therefore, as shown... Figure 11 As shown, the sample display area includes a sample list display area 1101 and a sample information display area 1102. The sample list in the sample list display area 1101 is grayed out (i.e., individual target samples cannot be edited), and the sample number in the sample information display area 1102 is displayed as "all samples".

[0169] In some examples, the sample editing interface in batch sample editing mode can also display a work editing area, showing newly added work nodes in response to the addition of new work nodes. For example, when there is a need to add work nodes, a work task box for confirmation can be added for the sample addition node, or a work task box for confirmation can be added for the cap opening node.

[0170] S811, in response to the user's project addition operation, displays the second detection item that needs to be detected for the virtual sample in the project editing area, and displays the available detection resources corresponding to the second detection item.

[0171] In batch sample editing mode, the user's editing commands (i.e. batch editing commands) are uniformly applied to the virtual samples. The mapping relationship between the virtual samples and multiple target samples synchronously maps the editing commands to each target sample associated with the virtual sample.

[0172] S812, determine the target detection resource selected by the user for the second detection item.

[0173] The selected target detection resource is chosen from the available detection resources.

[0174] S813, for each target sample associated with the virtual sample, a detection task corresponding to the second detection item is generated, and the detection task of each target sample is bound to the target detection resource.

[0175] Each target sample associated with the virtual sample has a corresponding detection task. Therefore, step S814 is executed for each target sample associated with the virtual sample.

[0176] S814 executes the detection task corresponding to the target sample, and forcibly schedules the target sample to the bound target detection resource.

[0177] S815 performs target sample detection based on target detection resources.

[0178] S816 feeds back the detection results to the upper layer.

[0179] The above solution enables the customization of target detection resources, meets the sample detection needs of complex and refined scenarios, and can improve the accuracy of sample detection.

[0180] In another aspect, this application provides a laboratory automation system, which includes a human-computer interaction device and a controller for providing a human-computer interaction interface. The controller includes a processor and a memory, and the memory stores a computer program. When the computer program is executed by the processor, it implements the various processes of the above-described sample detection method embodiments.

[0181] In another aspect, this application provides an electronic device including a processor and a memory connected to the processor. The memory stores a computer program that can be executed by the processor. When the computer program is executed by the processor, it implements various processes of the sample detection method embodiment.

[0182] In another aspect, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the various processes of the above-described sample detection method embodiments. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0183] In another aspect, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the various processes of the above-described sample detection method embodiments.

[0184] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0185] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0186] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A sample detection method, characterized in that, The method is applied to a laboratory automation system, which provides a human-machine interface; the method includes: In response to an editing command triggered on a target sample in a human-computer interaction interface, a test task corresponding to a detection item of the target sample is generated; the editing command includes specifying a target detection resource for the detection item; the detection item is at least one, and the test task corresponding to each detection item is bound to the specified target detection resource; The target sample is scheduled to the bound target detection resource based on the test task to perform detection on the detection item corresponding to the test task.

2. The method according to claim 1, characterized in that, The target detection resources include at least one of the following: detection instrument serial number, reagent kit box number, or reagent kit batch number.

3. The method according to claim 1, characterized in that, The human-computer interaction interface displays at least one detection item for editing the target sample and the specified target detection resource; The first detection item that has been completed in at least one detection item has a corresponding copy control; The method further includes: In response to the triggering of the copy control, a new test task is generated for the first detection item; The newly added test task carries at least a portion of the original detection resources corresponding to the first detection item; the original detection resources refer to the target detection resources corresponding to the first detection item in the completed detection.

4. The method according to claim 1, characterized in that, The method further includes: If the target sample has at least one second detection item that failed to be detected, a corresponding retest task box to be confirmed is generated for each second detection item in the human-computer interaction interface.

5. The method according to claim 4, characterized in that, The pending retest task box is configured to automatically populate the target detection resource corresponding to the second detection item when the detection fails. or, The pending retest task box is configured to automatically fill in at least one detection resource that is different from the target detection resource corresponding to the failure of the second detection item.

6. The method according to claim 1, characterized in that, The target sample has a corresponding scheduling strategy; the scheduling strategy includes at least one working node; the editing instruction is also used to indicate the working node to be changed for the target sample; the working node to be changed includes a newly added working node and / or a working node to be deleted; The method further includes: Update the scheduling strategy of the target sample based on the work node to be changed; The execution path of the target sample is controlled based on the updated scheduling strategy.

7. The method according to claim 6, characterized in that, The method further includes: Based on the current cap status of the target sample, a task box to be confirmed is automatically generated in the human-computer interaction interface; wherein, the task box to be confirmed includes a sample addition node and an opening node generated when the cap status is capped. The step of updating the scheduling strategy of the target sample based on the working node to be changed includes: The scheduling strategy for the target sample is updated based on the confirmed work nodes in the task to be confirmed box and the work nodes to be changed indicated by the editing command.

8. The method according to claim 7, characterized in that, The editing command is used to indicate the second working node to be added for the target sample; The method further includes: If the editing instruction is received during the execution of the target sample in the first working node, the updated scheduling strategy is analyzed after the first working node is completed. When the currently pending work node in the updated scheduling policy is the newly added second work node, the execution of the second work node is triggered.

9. The method according to claim 7, characterized in that, The worker node to be changed includes at least one newly added worker node; updating the scheduling policy of the target sample based on the worker node to be changed includes: Traverse the at least one new working node. If the currently traversed new working node has a corresponding historical working node in the scheduling policy of the target sample that is in an unexecuted state, then one of the new working node and the corresponding historical working node is retained in the scheduling policy. Alternatively, the new working node and the corresponding historical working node are retained in the scheduling policy, but one of the new working node and the historical working node is in a shelved state. The working node in the shelved state will not be actually executed.

10. The method according to claim 7, characterized in that, The updated scheduling strategy includes the addition of new working nodes; The step of controlling the execution path of the target sample based on the updated scheduling strategy includes: When the target sample is scheduled to execute the newly added working node based on the updated scheduling strategy, it is determined whether the newly added working node conflicts with the current state of the target sample; the current state includes the cap state and / or the working node execution state. If there is a conflict, the newly added work node to be executed will be skipped, and the subsequent work nodes in the scheduling strategy will continue to be executed.

11. The method according to any one of claims 1 to 10, characterized in that, There are multiple target samples; virtual samples are created for each of the multiple target samples to uniformly receive the editing instructions; the editing instructions triggered by the virtual samples are batch editing instructions; a mapping relationship is established between the virtual samples and the multiple target samples to be processed in batches; the batch editing instructions triggered by the virtual samples are synchronously mapped to each target sample associated with the virtual samples.

12. The method according to claim 11, characterized in that, The step of generating a test task corresponding to the detection items of the target sample in response to an editing command triggered on the human-computer interaction interface includes: In response to a batch editing command triggered for the virtual sample, it is determined whether a first target sample exists among a plurality of target samples associated with the virtual sample; wherein the first target sample already has an unexecuted first detection task corresponding to the detection item specified by the batch editing command; and the target samples other than the first target sample among the plurality of target samples are second target samples. If so, for each of the first target samples, the batch editing instructions are synchronously mapped to the first target sample to generate a second test task corresponding to the specified detection item of the first target sample, and the second detection task and the first detection task are deduplicated; or, the batch editing instructions are not synchronously mapped to the first target sample. For each of the second target samples, the batch editing instructions are synchronously mapped to the second target samples to generate a test task corresponding to the specified detection items of the second target samples.

13. The method according to any one of claims 1 to 10, characterized in that, The step of scheduling the target sample to the bound target detection resource based on the test task to perform detection on the detection item corresponding to the test task includes: When the sampling node in the scheduling strategy of the target sample is executed, the target sample is scheduled to the target detection resource based on the test task, and the sampling process is performed to perform detection on the detection item corresponding to the test task.

14. A laboratory automation system, the system comprising a human-machine interface device and a controller for providing a human-machine interface, characterized in that, The controller includes a processor and a memory, the memory storing a computer program that, when executed by the processor, implements the steps of the method as described in any one of claims 1 to 13.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 13.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 13.

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