Robust sparse sample misidentification method and system with multi-stage progressive exclusion and validation

Abstract

The application discloses a kind of multi-stage progressive exclusion and verification robust sparse sample mixed detection method and system, belong to popular disease early infection screening technical field.The method includes: according to the mixed detection parameter of screening scene setting;Subsequently enter multi-stage detection process, according to the current sample quantity to be detected in each stage, dynamically adjust mixed pool scale and detection times, and according to the detection result, sample is continuously classified and screened, and gradually exclude definite negative sample, while directly lock part of definite positive sample by analyzing the remaining sample in positive pool;Finally, the remaining sample is detected separately, and the identification of all positive samples is completed.The present application effectively copes with the uncertainty in actual detection through the robust multi-stage progressive design and dynamic adjustment mechanism, while ensuring the detection efficiency, significantly improves the detection rate of low viral load samples, has the characteristics of strong implementability and wide adaptability, and is suitable for large-scale sparse sample detection scene.

Description

Technical Field

[0001] This invention belongs to the field of early-stage screening technology for infectious diseases, specifically involving a robust sparse sample pooling method and system with multi-stage progressive exclusion and verification. Through a multi-stage dynamic adjustment mechanism and robust judgment rules, the sensitivity and reliability of the detection are improved, and it is especially suitable for the accurate detection of low viral load samples in large-scale sparse sample scenarios. Background Technology

[0002] In early screening for an epidemic, the population positivity rate was extremely low, and the number of positive samples was very small. Much smaller than the total number of samples ( Pooled testing, by combining multiple samples for testing, can significantly reduce the number of tests, reagent consumption, and testing costs, making it a core technology choice in this scenario. However, existing pooled testing technologies still have two major drawbacks that seriously affect testing accuracy and efficiency.

[0003] First, samples with low viral loads have a high risk of false negatives. The viral load in these samples is close to the detection limit of the testing reagent. During pooled testing, due to dilution from multiple negative samples, the viral load can easily drop below the detection limit, making the test reagent unable to identify the sample and resulting in false negatives. Existing pooled testing methods typically employ a fixed-size pooling strategy, lacking targeted robust design and failing to prevent false negatives due to over-dilution at the algorithmic level.

[0004] Secondly, traditional pooled testing strategies lack dynamic adaptability. In existing methods, core parameters such as pool size and number of tests are usually set to fixed values ​​based on experience, failing to dynamically adjust according to the current number of samples to be tested. When the number of samples to be tested decreases significantly, continuing to use the initial pooling parameters will further exacerbate the risk of dilution of low viral load samples; conversely, if parameter adjustments lack a systematic basis, it can easily lead to wasted testing resources or incomplete screening coverage, making it difficult to flexibly adapt to changes in sample size during actual screening.

[0005] Furthermore, existing methods employ a single sample selection strategy, typically using random or fixed-order mixing. They lack a mechanism for tracking and balancing the historical participation of samples, which can easily lead to some samples being mixed repeatedly while others are not sufficiently involved. This makes it difficult to ensure the uniformity and fairness of sample coverage during the screening process, thereby affecting the stability and reliability of the overall test results.

[0006] Therefore, there is an urgent need for a pooled testing method that is both robust and dynamically adaptable, optimizing the entire process from sample selection and parameter adjustment to result determination, to solve the above-mentioned technical pain points and achieve efficient and accurate screening of large-scale sparse samples. Summary of the Invention

[0007] To address the problems in the prior art, this invention proposes a robust sparse sample pooling method and system with multi-stage progressive exclusion and verification.

[0008] The technical solution adopted in this invention is as follows:

[0009] In a first aspect, the present invention discloses a robust sparse sample pooling method with multi-stage progressive exclusion and verification, comprising the following steps:

[0010] S1: Collection Each sample to be tested is numbered, and an equal amount of [unspecified substance] is prepared for each sample. share;

[0011] S2: Set the maximum mixing pool size Minimum mixing pool size The maximum number of times each sample can be mixed. Clearly define the threshold for negative result determination. Define the sample state vector. And initialize, where The state of sample number i is represented, where the state includes four types: negative, clearly positive, suspected positive, and pending; a cumulative negative pool count vector is defined. Positive pool record set Cumulative Mixed Quantity Vector ;

[0012] S3: The detection process includes several detection stages performed sequentially in chronological order, defining the... Phased sample collection Mixing pool size Number of mixed detections ; Define the first Stage Sample Mixing Matrix ; Define the first Phase detection result vector Used to record the state of the mixing pool; in the first Each testing phase is executed. Sub-sample mixing operation;

[0013] Each sample pooling operation filters out samples with a status of suspected positive and pending from all samples, provided the number of pooling operations is less than [number missing]. The samples constitute the set of samples to be tested. The size of the mixing tank is determined based on the number of samples to be tested. and number of tests Select from the set of samples to be tested Mix the samples and update the mixing matrix. ;

[0014] S4: Detect the state of the mixing pool and update the variables;

[0015] Detection Record the state of each mixed pool, check the detection results, and update the cumulative negative pool count vector. Positive pool record set Cumulative Mixed Quantity Vector Update sample status Update the positive pool record set according to the latest sample status. ;

[0016] calculate Size of the sample set to be tested in the stage If the termination condition is met, proceed to S5; otherwise, return to S3 and continue with the sample mixing operation in the next detection stage.

[0017] S5: Define the final set of samples to be verified ,right All samples are tested individually, and the results are output as samples that test positive on a single test and samples that are clearly positive.

[0018] Secondly, the present invention provides a robust sparse sample pooling system for implementing the above-described method, comprising: a sample preprocessing module, a parameter setting module, a sample dynamic pooling module, a detection update module, a stage termination judgment module, and a verification module; the sample preprocessing module is used to number the collected samples and prepare an equal amount of each sample. The parameter setting module sets the maximum mixing pool size. Minimum mixing pool size The maximum number of times each sample can be mixed. Clearly define the threshold for negative result determination. Initialize the sample state vector Cumulative negative pool count vector Cumulative Mixed Count Vector Positive pool record set Initialize the first Phased sample collection Mixing pool size Number of mixed detections Sample mixing matrix Detection result vector The sample dynamic mixing module executes at each stage. The sample pooling operation is performed in multiple steps; in each pooling operation, samples with a status of suspected positive or pending are selected from all samples, and the number of pooling operations is less than [number missing]. The samples constitute the set of samples to be tested. The size of the mixing tank is determined based on the number of samples to be tested. and number of tests Select from the set of samples to be tested Mix the samples and update the mixing matrix. The detection and update module is used for detection. Record the state of each mixed pool, check the detection results, and update the cumulative negative pool count vector. Positive pool record set Cumulative Mixed Quantity Vector Update sample status according to rules The positive pool record set is updated based on the latest sample status. The stage termination judgment module calculates the number of samples to be tested in the next stage and determines whether the termination condition is met. If it is met, the module proceeds to the verification module; otherwise, the dynamic sample mixing module is called to continue the sample mixing operation in the next stage. The verification module is used to verify the final set of samples to be tested. All samples are tested individually, and the results are output as samples that test positive on a single test and samples that are clearly positive.

[0019] Thirdly, the present invention discloses an electronic device, including a processor and a memory, wherein the memory stores machine-executable instructions that can be executed by the processor, and the processor executes the machine-executable instructions to implement the robust sparse sample pooling method of multi-stage progressive exclusion and verification.

[0020] Fourthly, the present invention discloses a machine-readable storage medium storing machine-executable instructions, which, when called and executed by a processor, are used to implement the robust sparse sample pooling method of multi-stage progressive exclusion and verification.

[0021] Compared with the prior art, the beneficial effects of the present invention include:

[0022] This invention, through systematic design, significantly improves the robustness of detection and effectively solves the problem of missed detection in samples with low viral load. This is achieved by introducing a clear negative threshold. It can filter out false negatives caused by dilution; at the same time, the size of the mixing tank... It can be dynamically adjusted according to the number of samples to be tested, reducing the degree of dilution from the source and greatly improving the detection rate of samples with low viral load.

[0023] Regarding dynamic adaptability, this invention utilizes the current number of samples to be tested. Real-time adjustment of core parameters (such as mixing pool size) Number of tests This system optimizes the sample mixing strategy. In the early stages of screening, when the sample size is large, a larger mixing pool is used to quickly remove negative samples, improving overall efficiency. In the later stages, when the sample size decreases, a smaller mixing pool is used, effectively avoiding the risk of over-dilution. This mechanism allows the testing process to closely match the dynamic changes in sample size during the actual screening process, overcoming the shortcomings of traditional methods such as fixed parameters and poor adaptability, and achieving a dynamic balance between efficiency and accuracy.

[0024] Furthermore, through a multi-stage progressive exclusion mechanism, a large number of clearly negative samples can be quickly screened out. At the same time, by analyzing the positive mixed pool, some clearly positive samples can be directly identified, so that subsequent testing resources can be concentrated on the analysis of suspected positive and pending samples, which significantly reduces invalid operations and repeated testing, and reduces reagent consumption and total testing time.

[0025] The implementation of this invention is flexible and controllable. The system supports two sample selection strategies: random selection and mixed-number equalization. Core parameters can be flexibly configured according to laboratory conditions, viral characteristics, and screening scale, requiring no hardware modification and facilitating widespread adoption. Therefore, this method can adapt to screening scenarios of different scales, positive rates, and viral load distributions. It is suitable for both high-throughput institutions and meets the rapid testing needs of grassroots units, possessing broad application value. Attached Figure Description

[0026] Figure 1 This is a flowchart of a robust sparse sample pooling process with multi-stage progressive exclusion and verification, as described in this invention.

[0027] Figure 2 This is a flowchart of a single detection stage of a robust sparse sample pooling method with multi-stage progressive exclusion and verification described in this invention.

[0028] Figure 3 The results show the comparative experimental results of the embodiments of the present invention and the traditional two-stage pooled testing method.

[0029] Figure 4 This is a schematic diagram of the robust sparse sample mixture detection system of the present invention. Detailed Implementation

[0030] The present invention will be further described and illustrated below with reference to specific embodiments. The technical features of each embodiment of the present invention can be combined accordingly, provided that there is no mutual conflict.

[0031] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

[0032] Figure 1 This is a flowchart of a hybrid detection method in a specific embodiment of the present invention. This embodiment starts from... Samples were collected from 100 subjects, of which the number of positive samples was [number missing]. Preferred number of positive samples It should be smaller than This requirement aligns with the characteristics of the early stages of an epidemic; therefore, the method of this invention is suitable for screening infected individuals in the early stages of an epidemic. The pooled testing method of this invention employs a multi-stage, progressive exclusion and verification approach, and its specific process is as follows:

[0033] S1: Collection Each sample to be tested is assigned a number, and a sample set is defined. The number of positive samples does not exceed Prepare an equal amount of each sample. share; The maximum number of times each sample can be mixed; each sample has the same viral load and is used for subsequent mixing operations.

[0034] S2: Set the maximum mixing pool size Minimum mixing pool size Clearly define the threshold for negative result determination. Define the sample state vector. Define the cumulative negative pool count vector. This is used to record the number of times each sample appears in the negative pool, initially set to all zeros; a cumulative mixing count vector is defined. This is used to record the number of times each sample has been mixed, initially set to all zeros; define the positive pool record set. This is used to record the sample set for each positive pool, initially an empty set;

[0035] It should be noted that the maximum mixing pool size Minimum mixing tank size All depend on the testing platform (such as laboratory testing equipment) and ; 0 indicates negative, 1 indicates positive, 2 indicates suspected positive, and 3 indicates pending; initial state. Clearly define the threshold for negative result determination. ;No. The set of samples to be tested in the stage , Number of mixed detections Mixing pool size .

[0036] S3: The detection process includes several detection stages performed sequentially in chronological order, defining the... Phased sample collection Its size is Mixing pool size Number of mixed detections ; Define the first Stage Sample Mixing Matrix Used to record the sample mixing process, initially an all-zero matrix; define the first... Phase detection result vector Used to record the state of the mixing pool (negative or positive), initially set to all zeros; in the... Each testing phase is executed. Sub-sample mixing operation;

[0037] Each sample pooling operation filters out samples with a status of suspected positive and pending from all samples, provided the number of pooling operations is less than [number missing]. The samples constitute the set of samples to be tested. The size of the mixing tank is determined based on the number of samples to be tested. and number of tests Select from the set of samples to be tested Mix the samples and update the mixing matrix. ;

[0038] In one embodiment of the present invention, step S3 specifically includes:

[0039] S31: In the Each stage, execution Sub-sample mixing operation;

[0040] S32: For the first Sub-sample mixing operation, where From all samples, those with a status of suspected positive and pending, and with a mixture count of less than [number missing], were selected. The samples constitute the set of samples to be tested. :

[0041] ;

[0042] In the formula: Indicates sample state, Indicates sample Number of times the mixture has been participated in;

[0043] S33: Based on the number of samples to be tested Determine the size of the mixing tank and number of mixed detections :

[0044] ,

[0045] ;

[0046] From the set of samples to be tested Select Mix the samples and update the mixing matrix. The Okay, this line has Each element corresponds to a sample number to be tested and participates in the mixing process. Each sample corresponds to Set one element to 1 and the rest to 0;

[0047] Specifically, one or a combination of the following strategies can be used to analyze the sample set to be tested. Select a sample:

[0048] Random selection strategy: Sample The probability of being selected is ;

[0049] Mixing frequency balancing strategy: To ensure that every sample can participate in the mixing process, samples with fewer historical mixing frequencies are prioritized. The probability of being selected is .

[0050] S34: Repeat steps S32-S33 until you get... Mixed samples.

[0051] S4: Detect the state of the mixing pool and update the variables;

[0052] Detection Record the state of each mixed pool, check the detection results, and update the cumulative negative pool count vector. Positive pool record set Cumulative Mixed Quantity Vector ;

[0053] Update sample status according to rules : Number of times the sample appears in the negative pool The time is recorded as a clear negative; the positive pool is recorded as a set. If there is only one sample remaining in the positive pool, the sample is marked as a clear positive; a sample that appears in at least one positive pool but is not marked as a clear positive or a clear negative is marked as a suspected positive; the remaining samples excluding the above three categories are marked as pending.

[0054] Update the positive pool record set according to the latest sample status. ;

[0055] calculate Size of the sample set to be tested in the stage If the termination condition is met, proceed to S5; otherwise, return to S3 and continue with the sample mixing operation in the next detection stage.

[0056] In one embodiment of the present invention, step S4 specifically includes:

[0057] S41: Yes The mixed samples were tested, the state of the mixing pool was recorded, and the detection result vector was updated. ,in Indicates the first One of the mixed pools tested positive. Indicates the first Each mixed pool is negative; update the cumulative negative pool count vector. :

[0058] ;

[0059] In the formula: Indicates sample The number of times it appears in the negative pool Represents the mixture matrix The OK,

[0060] No. Column elements, express The first vector One element, symbol This indicates an indicator function that responds to any condition or event. , exist The value is 1 if the condition is met, and 0 otherwise.

[0061] Update the positive pool record set ,in express The corresponding sample set at that time;

[0062] Update the cumulative mixing frequency vector : ,in Indicates sample Number of times the mixture has been participated in;

[0063] S42: Update sample status according to rules:

[0064] Clearly negative ( ):sample The number of times it appears in the negative pool satisfies When the threshold is reached, it is recorded as a clear negative; Filter low viral load samples that were mistakenly identified as negative due to dilution;

[0065] Clearly positive ( ):exist satisfy That is, the positive pool sample set If there is only one sample, that sample is recorded as a definite positive.

[0066] Suspected positive ( ):sample Appearing in at least one In, and not marked as or Such samples carry a risk of being positive and are recorded as suspected positive.

[0067] Pending ( The remaining samples after excluding the above three states are marked as pending and require further verification in subsequent stages;

[0068] S43: Update the positive pool record set Remove each positive pool sample set China has been marked as ;

[0069] S44: No. The set of samples to be tested in the stage Its size is ,like Then proceed to step S5; otherwise... Return to step S3 to continue with the next stage of sample mixing.

[0070] S5: Define the final set of samples to be verified ,right All samples are tested individually, and the results are output as samples that test positive on a single test and samples that are clearly positive.

[0071] This invention uses large-scale community-based epidemiological screening as an application scenario, and the specific process is as follows:

[0072] Total number of samples to be tested The sample set is The number of positive samples The viral load in positive samples follows Uniform distribution; prepare equal amounts of each sample Set up Each sample contains the same viral load and is used for subsequent mixing operations.

[0073] Set the core parameters according to the scenario requirements: maximum mixing pool size Minimum mixing pool size The maximum number of times each sample can be mixed. Clearly define the threshold for negative result determination. The detection limit (LOD) of the reagent is 100 copies / ml. If the viral load in the mixing chamber is less than the LOD, the test in that chamber is negative; otherwise, it is positive. Initialize the sample state vector. (1000-dimensional) Cumulative negative pool count vector (1000-dimensional) cumulative mixing frequency vector (1000-dimensional) Positive pool record set ; Define the first Phased sample collection Its size is Mixing pool size Number of mixed detections Sample mixing matrix Detection result vector ; No. The set of samples to be tested in the stage , Number of mixed detections Mixing pool size .

[0074] Figure 3 This comparison shows the total number of tests performed under the same experimental conditions between the embodiments of this invention and traditional two-stage pooled testing methods. Each method was independently repeated 100 times to calculate the mean and variance of the total number of tests. The two-stage pooled testing method involves mixing samples at a fixed pool size (5-to-1, 10-to-1, or 20-to-1, corresponding to 5 / 1, 10 / 1, and 20 / 1 in the illustration), followed by individual testing of samples in the positive pool in the second stage. Experimental results show that the average number of testing stages for the multi-stage method of this invention is 3.2, and the average total number of tests is significantly lower than all two-stage pooled testing methods with fixed pool sizes. This invention effectively reduces redundant testing operations by dynamically adjusting the pool size and gradually excluding samples with known states, thereby significantly improving testing efficiency in large-scale sample screening scenarios.

[0075] Figure 4This is a schematic diagram of the robust sparse sample mixing detection system of the present invention. The mixing detection system of the present invention is used to implement the mixing detection method in the foregoing embodiments, and includes:

[0076] Sample preprocessing module: Numbers the collected samples and prepares an equal amount of sample preprocessing. share;

[0077] Parameter setting module: Sets the maximum mixing pool size Minimum mixing pool size The maximum number of times each sample can be mixed. Clearly define the threshold for negative result determination. ; Initialize the first Phased sample collection Mixing pool size Number of mixed detections Sample mixing matrix Detection result vector Initialize the cumulative negative pool count vector. Cumulative mixing frequency vector Positive pool record set ;

[0078] Sample dynamic mixing module: Execution at each stage The sample pooling operation is performed in multiple steps; in each pooling operation, samples with a status of suspected positive or pending are selected from all samples, and the number of pooling operations is less than [number missing]. The samples constitute the set of samples to be tested. The size of the mixing tank is determined based on the number of samples to be tested. and number of tests Select from the set of samples to be tested Each sample is combined and the mixture is updated. ;

[0079] Detection and update module: Detection Record the state of each mixed pool, check the detection results, and update the cumulative negative pool count vector. Positive pool record set Cumulative Mixed Quantity Vector Update sample status according to rules The positive pool record set is updated based on the latest sample status. ;

[0080] Stage Termination Judgment Module: Calculates the number of samples to be tested in the next stage, determines whether the termination condition is met, and if it is met, proceeds to the verification module; otherwise, it calls the sample dynamic mixing module to continue the sample mixing operation in the next stage.

[0081] Validation module: Defines the final set of samples to be validated. ,right All samples are tested individually, and the results are output as samples that test positive on a single test and samples that are clearly positive.

[0082] This invention also provides an electronic device, including a memory and a processor;

[0083] The memory is used to store computer programs;

[0084] The processor is configured to implement the robust sparse sample pooling method described above, which involves multi-stage progressive exclusion and verification, when executing the computer program.

[0085] This invention also provides a computer-readable storage medium storing a program that, when executed by a processor, implements the aforementioned robust sparse sample pooling method with multi-stage progressive exclusion and verification.

[0086] The computer-readable storage medium can be an internal storage unit of any data processing device described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device of any data processing device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units and external storage devices of any data processing device. The computer-readable storage medium is used to store the computer program and other programs and data required by the data processing device, and can also be used to temporarily store data that has been output or will be output.

[0087] Obviously, the embodiments and accompanying drawings described above are merely some examples of this application. Those skilled in the art can apply this application to other similar situations based on these drawings without any creative effort. Furthermore, it is understood that although the work done in this development process may be complex and lengthy, for those skilled in the art, certain design, manufacturing, or production modifications made based on the technical content disclosed in this application are merely conventional technical means and should not be considered as insufficient disclosure of this application. Several modifications and improvements can be made without departing from the concept of this application, and these all fall within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims

1. A robust sparse sample pooling method with multi-stage progressive exclusion and verification, characterized in that: Includes the following steps: S1: Collection Each sample to be tested is numbered, and an equal amount of [unspecified substance] is prepared for each sample. share; S2: Set the maximum mixing pool size Minimum mixing pool size The maximum number of times each sample can be mixed. Clearly define the threshold for negative result determination. Define the sample state vector. And initialize, where This indicates the status of sample number i, which includes four statuses: negative, clearly positive, suspected positive, and pending. Define the cumulative negative pool count vector Positive pool record set Cumulative Mixed Quantity Vector ; S3: The detection process includes several detection stages performed sequentially in chronological order, defining the... Phased sample collection Mixing pool size Number of mixed detections ; Define the first Stage Sample Mixing Matrix ; Define the first Phase detection result vector Used to record the state of the mixing pool; in the first Each testing phase is executed. Sub-sample mixing operation; Each sample pooling operation filters out samples with a status of suspected positive and pending from all samples, provided the number of pooling operations is less than [number missing]. The samples constitute the set of samples to be tested. The size of the mixing tank is determined based on the number of samples to be tested. and number of tests Select from the set of samples to be tested Mix the samples and update the mixing matrix. ; S4: Detect the state of the mixing pool and update the variables; Detection Record the state of each mixed pool, check the detection results, and update the cumulative negative pool count vector. Positive pool record set Cumulative Mixed Quantity Vector Update sample status Update the positive pool record set according to the latest sample status. ; calculate Size of the sample set to be tested in the stage If the termination condition is met, proceed to S5; otherwise, return to S3 and continue with the sample mixing operation in the next detection stage. S5: Define the final set of samples to be verified ,right All samples are tested individually, and the results are output as samples that test positive on a single test and samples that are clearly positive.

2. The robust sparse sample pooling method with multi-stage progressive exclusion and verification as described in claim 1, characterized in that: Step S1 specifically includes: S11: Collection A sample set is defined as a set of samples to be tested. The number of positive samples Less than ; S12: Prepare an equal amount of each sample Each portion contains the same viral load and is used for subsequent mixing operations.

3. The robust sparse sample pooling method with multi-stage progressive exclusion and verification according to claim 2, characterized in that: In step S2, the maximum mixing pool size Minimum mixing tank size satisfy: ; 0 indicates negative, 1 indicates positive, 2 indicates suspected positive, and 3 indicates pending; initial state. Clearly define the threshold for negative result determination. ;No. The set of samples to be tested in the stage , Number of mixed detections Mixing pool size .

4. The robust sparse sample pooling method with multi-stage progressive exclusion and verification according to claim 3, characterized in that: Step S3 specifically includes: S31: In the Each stage, execution Sub-sample mixing operation; S32: For the first Sub-sample mixing operation, where From all samples, those with a status of suspected positive and pending, and with a mixture count of less than [number missing], were selected. The samples constitute the set of samples to be tested. : ； In the formula: Indicates sample state, Indicates sample Number of times the mixture has been participated in; S33: Based on the number of samples to be tested Determine the size of the mixing tank and number of mixed detections : ， ； From the set of samples to be tested Select Mix the samples and update the mixing matrix. The Okay, this line has Each element corresponds to a sample number to be tested and participates in the mixing process. Each sample corresponds to Set one element to 1 and the rest to 0; S34: Repeat steps S32-S33 until you get... A mixed sample.

5. The robust sparse sample pooling method with multi-stage progressive exclusion and verification according to claim 4, characterized in that: In step S33, one or a combination of the following strategies are used to select samples from the test sample set. Select a sample: Random selection strategy: Sample The probability of being selected is ; Mixing frequency balancing strategy: Prioritize samples with fewer historical mixing frequencies. The probability of being selected is .

6. The robust sparse sample pooling method with multi-stage progressive exclusion and verification according to claim 5, characterized in that: Step S4 specifically includes: S41: Yes The mixed samples were tested, the state of the mixing pool was recorded, and the detection result vector was updated. ,in Indicates the first One of the mixed pools tested positive. Indicates the first Each mixed pool is negative; update the cumulative negative pool count vector. : ； In the formula: Indicates sample The number of times it appears in the negative pool Represents the mixture matrix The OK, No. Column elements, express The first vector One element, symbol This indicates an indicator function that responds to any condition or event. , exist The value is 1 if the condition is met, and 0 otherwise. Update the positive pool record set ,in express The corresponding sample set at that time; Update the cumulative mixing frequency vector : ,in Indicates sample Number of times the mixture has been participated in; S42: Update sample status: the number of times the sample appears in the negative pool. The time is recorded as a clear negative; the positive pool is recorded as a set. If there is only one sample remaining in the positive pool, the sample is marked as a clear positive; a sample that appears in at least one positive pool but is not marked as a clear positive or a clear negative is marked as a suspected positive; the remaining samples excluding the above three categories are marked as pending. S43: Update the positive pool record set Remove each positive pool sample set China has been marked as ; S44: No. The set of samples to be tested in the stage Its size is ,like Then proceed to step S5; otherwise... Return to step S3 to continue with the next stage of sample mixing.

7. The robust sparse sample pooling method with multi-stage progressive exclusion and verification according to claim 6, characterized in that: Step S42 specifically includes: Clearly negative: Sample The number of times it appears in the negative pool satisfies When the threshold is reached, it is recorded as a clear negative; Filter low viral load samples that were mistakenly identified as negative due to dilution; Clearly positive: present satisfy That is, the positive pool sample set If there is only one sample, that sample is recorded as a definite positive. Suspicious positive: Sample Appearing in at least one In, and not marked as or Such samples carry a risk of being positive and are recorded as suspected positive. Pending: The remaining samples after excluding the above three states are marked as pending and require further verification in subsequent stages.

8. A robust sparse sample pooling system implementing the method of any one of claims 1-7, characterized in that, include: Sample preprocessing module: Numbers the collected samples and prepares an equal amount of sample preprocessing. share; Parameter setting module: Sets the maximum mixing pool size Minimum mixing pool size The maximum number of times each sample can be mixed. Clearly define the threshold for negative result determination. ; Initialize the first Phased sample collection Mixing pool size Number of mixed detections Sample mixing matrix Detection result vector ; Initialize the cumulative negative pool count vector Cumulative Mixed Count Vector Positive pool record set ; Sample dynamic mixing module: Execution at each stage The sample pooling operation is performed in multiple steps; in each pooling operation, samples with a status of suspected positive or pending are selected from all samples, and the number of pooling operations is less than [number missing]. The samples constitute the set of samples to be tested. The size of the mixing tank is determined based on the number of samples to be tested. and number of tests Select from the set of samples to be tested Mix the samples and update the mixing matrix. ; Detection and update module: Detection Record the state of each mixed pool, check the detection results, and update the cumulative negative pool count vector. Positive pool record set Cumulative Mixed Quantity Vector Update sample status according to rules The positive pool record set is updated based on the latest sample status. ; Stage Termination Judgment Module: Calculates the number of samples to be tested in the next stage, determines whether the termination condition is met, and if it is met, proceeds to the verification module; otherwise, it calls the sample dynamic mixing module to continue the sample mixing operation in the next stage. Validation module: Defines the final set of samples to be validated. ,right All samples are tested individually, and the results are output as samples that test positive on a single test and samples that are clearly positive.

9. An electronic device, characterized in that, The method includes a processor and a memory, the memory storing machine-executable instructions that can be executed by the processor, the processor executing the machine-executable instructions to implement the robust sparse sample pooling method of multi-stage progressive exclusion and verification as described in any one of claims 1 to 8.

10. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores machine-executable instructions that, when called and executed by a processor, are used to implement the robust sparse sample pooling method of multi-stage progressive exclusion and verification as described in any one of claims 1 to 8.

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