A data collection method and system for laboratory information system

Abstract

The present invention relates to the field of laboratory data acquisition technology, and in particular to a data acquisition method and system for a laboratory information system. The present invention determines the experimental parameters of a current sample through the experimental parameters of historical samples with similar experimental purposes as the current experiment; determines the universality of the experimental parameters according to the frequency of occurrence of each experimental parameter in a reference sample; calculates the researchers' attention to the experimental parameters by analyzing the performance of each experimental parameter in the experimental analysis of the reference sample; and finally calculates the importance of the experimental parameters to the current sample according to their universality and attention, thereby setting the sampling frequency of the parameters. The method and system of the present invention improve the scientificity and rationality of the sampling frequency of the experimental parameters and ensure the accuracy of the experimental results.

Description

Technical Field

[0001] The present invention relates to the technical field of laboratory data collection, and in particular to a data collection method and system for a laboratory information system. Background Art

[0002] The laboratory information system is an important means of modern laboratory management, which includes sample management, data management and resource management. It can improve work efficiency, ensure data quality, and enhance management level. At the same time, it can determine the sampling frequency of samples based on the experimental parameters in historical records.

[0003] The sampling frequency of experimental parameters is usually determined by analyzing the number of times the experimental parameters appear in historical samples similar to the current samples, ignoring the relationship between the experimental parameters and the samples. When analyzing soil samples, the formation, development, and characteristics of soil vary greatly under different climatic conditions. For example, in humid climate zones, researchers may pay more attention to soil drainage and air permeability, because excessive precipitation may cause water accumulation in the soil and affect plant growth; while in arid climate zones, soil moisture content becomes a key parameter. Therefore, for soil samples in different regions, researchers pay different attention to the parameters in the experimental samples, and the importance of the experimental parameters to the samples is different. If the importance of the experimental parameters is determined only by the number of times the experimental parameters appear, it is inaccurate for soil sample experiments. Summary of the invention

[0004] In order to solve the above technical problems, the object of the present invention is to provide a data acquisition method and system for a laboratory information system.

[0005] According to a first aspect of an embodiment of the present invention, a data collection method for a laboratory information system is provided, and the technical solution adopted is specifically as follows:

[0006] Obtaining the experimental report data of historical samples, the experimental report data including the sample source, experimental purpose, experimental parameters, and experimental analysis, and obtaining the sample source and experimental purpose of the current sample;

[0007] Analyze the similarity of the experimental purpose between all the historical samples and the current sample to obtain a reference sample, and determine the experimental parameters of the current sample based on the experimental parameters of the reference sample;

[0008] Based on the experimental parameters of the reference sample, analyzing the occurrence frequency of the experimental parameters of the current sample to obtain the universality of the experimental parameters;

[0009] Based on the sample source, the possibility that the current sample and the reference sample are located in the same region is analyzed to obtain a target sample, and the frequency of occurrence of the experimental parameters of the current sample in the experimental analysis of the target sample is analyzed, and the attention degree of the experimental parameters is obtained by combining the similarity of the experimental purpose between the target sample and the current sample;

[0010] According to the prevalence and attention of the experimental parameters, the importance of the experimental parameters is obtained;

[0011] The sampling frequency of the experimental parameters is set according to the importance of the experimental parameters.

[0012] In some embodiments of the present invention, analyzing the similarity of experimental purpose between all the historical samples and the current sample to obtain a reference sample includes:

[0013] Obtaining the experimental purpose sentence vectors of the historical sample and the current sample;

[0014] Calculating the similarity of the experimental purpose between the historical sample and the current sample according to the experimental purpose sentence vector;

[0015] A similarity threshold for the experimental purpose is set, and a reference sample is obtained according to the similarity for the experimental purpose.

[0016] In some embodiments of the present invention, determining the experimental parameters of the current sample based on the experimental parameters of the reference sample includes:

[0017] Obtaining the experimental parameters appearing in the experimental reports of all the reference samples to obtain the proposed experimental parameters of the current sample;

[0018] Analyze the consistency between any two detection elements of the proposed experimental parameters to obtain the similarity of the experimental parameters;

[0019] Based on the similarity of the experimental parameters, cluster analysis is performed on the proposed experimental parameters to obtain experimental parameter clusters;

[0020] The cluster center experimental parameters of the experimental parameter clustering cluster are extracted to determine the experimental parameters of the current sample.

[0021] In some embodiments of the present invention, analyzing the consistency between any two detection elements of the proposed experimental parameters to obtain the similarity of the experimental parameters includes:

[0022] The similarity of the names of any two of the proposed experimental parameters is analyzed, and the similarity of the elements between the detection element sequences corresponding to any two of the proposed experimental parameters is analyzed, and the similarity of the experimental parameters is obtained in combination with the length of the detection element sequence corresponding to the proposed experimental parameters.

[0023] In some embodiments of the present invention, based on the source of the sample, analyzing the possibility that the current sample and the reference sample are located in the same region to obtain the target sample includes:

[0024] Based on the sample sources of the current sample and the reference sample, obtaining the regional locations of the current sample and the reference sample;

[0025] Analyze the longitude and latitude distance relationship and the altitude relationship between the regional locations of the current sample and the reference sample to obtain the possibility that the current sample and the reference sample are located in the same region;

[0026] A possibility threshold is set, and a target sample is obtained based on the possibility.

[0027] In some embodiments of the present invention, analyzing the frequency of occurrence of the experimental parameter of the current sample in the experimental analysis of the target sample includes:

[0028] Obtaining a word segmentation sequence in an experimental analysis of the target sample;

[0029] Analyzing the segmentation similarity between the segmentation sequence and the experimental parameters of the current sample;

[0030] Setting a segmentation similarity threshold, and obtaining the experimental parameter segmentation in the experimental analysis of the target sample according to the segmentation similarity;

[0031] Analyzing a first ratio relationship between the number of times the experimental parameter segmentation appears in the experimental analysis of the target sample and the total number of all experimental parameter segmentations in the experimental analysis of the target sample, and analyzing a second ratio relationship between the mean number of times all detection elements corresponding to the experimental parameter segmentation appear in the experimental analysis of the target sample and the total number of all experimental parameter segmentations in the experimental analysis of the target sample;

[0032] The first ratio relationship and the second ratio relationship are combined to obtain the occurrence frequency of the experimental parameter of the current sample in the experimental analysis of the target sample.

[0033] In some embodiments of the present invention, a weight is set for the frequency of occurrence of the experimental parameters of the current sample in the experimental analysis of the target sample, and the weight coefficient is the similarity of the experimental purpose between the target sample and the current sample. The average is calculated by traversing all the target samples to obtain the attention of the experimental parameters.

[0034] In some embodiments of the present invention, the sampling frequency of the experimental parameter is set according to the importance of the experimental parameter, including:

[0035] Sort the experimental parameters from most important to least important;

[0036] Before The experimental parameters are used as the actual experimental parameters of the current sample;

[0037] Set the sampling frequency of the actual experimental parameters to The attention level of the experimental parameter is rounded up to an integer value.

[0038] According to a second aspect of an embodiment of the present invention, a data acquisition system for a laboratory information system is provided, comprising: a memory and a processor, wherein:

[0039] The memory is used to store program code;

[0040] The processor is used to read the program code stored in the memory and execute the method described in the first aspect of the embodiment of the present invention.

[0041] In some embodiments of the present invention, the processor comprises:

[0042] The experimental report acquisition module is used to obtain the experimental report data of historical samples, wherein the experimental report data includes the sample source, experimental purpose, experimental parameters, and experimental analysis, and simultaneously obtain the sample source and experimental purpose of the current sample;

[0043] An experimental parameter determination module, used to analyze the similarity of the experimental purpose between all the historical samples and the current sample, obtain a reference sample, and determine the experimental parameters of the current sample based on the experimental parameters of the reference sample;

[0044] The experimental parameter analysis module is used to analyze the occurrence frequency of the experimental parameters of the current sample based on the experimental parameters of the reference sample to obtain the universality of the experimental parameters; and based on the source of the sample, analyze the possibility that the current sample and the reference sample are located in the same area to obtain the target sample, analyze the occurrence frequency of the experimental parameters of the current sample in the experimental analysis of the target sample, and obtain the attention of the experimental parameters in combination with the similarity of the experimental purpose between the target sample and the current sample; and obtain the importance of the experimental parameters according to the universality and attention of the experimental parameters;

[0045] The sampling frequency determination module is used to set the sampling frequency of the experimental parameters according to the importance of the experimental parameters.

[0046] Compared with the prior art, the data collection method and system for laboratory information system provided by the present invention have the following beneficial effects:

[0047] The present invention obtains a reference sample by analyzing the similarity of the experimental purpose between all historical samples and the current sample, determines the experimental parameters of the current sample based on the experimental parameters of the reference sample, and improves the comprehensiveness and accuracy of the experimental parameters of the current sample by referring to the historical samples. Based on the experimental parameters of the reference sample, the frequency of occurrence of the experimental parameters of the current sample is analyzed to obtain the universality of the experimental parameters; the possibility of the current sample and the reference sample being located in the same region is analyzed to obtain the target sample, the frequency of occurrence of the experimental parameters of the current sample in the experimental analysis of the target sample is analyzed, and the attention of the experimental parameters is obtained by combining the similarity of the experimental purpose between the target sample and the current sample. By referring to the frequency of occurrence of the experimental parameters in the experimental analysis in the target sample located in the same region as the current sample, the attention of the experimental parameters obtained is more real and reliable. Finally, the universality and attention of the experimental parameters are combined to obtain the importance of the experimental parameters, and the sampling frequency of the experimental parameters is set. The sampling frequency set based on the importance of the experimental parameters not only takes into account the universality of the experimental parameters in similar experiments, but also takes into account the importance of the experimental parameters being concerned under different climate conditions in different regions, improves the scientificity and rationality of the sampling frequency of the experimental parameters, and ensures the accuracy of the experimental results. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 A basic flow chart of a data collection method for a laboratory information system provided by an embodiment of the present invention;

[0050] Figure 2 A schematic diagram of a basic flow chart for determining experimental parameters of a current sample provided by an embodiment of the present invention;

[0051] Figure 3 A basic flow chart of a method for analyzing the degree of attention of experimental parameters provided by one embodiment of the present invention;

[0052] Figure 4 A schematic diagram of the basic composition of a data acquisition system for a laboratory information system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a data acquisition method and system for a laboratory information system proposed by the present invention, its specific implementation method, structure, features and effects, in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. Terms such as "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of further restrictions, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the article or device including the element.

[0055] A specific scheme of a data collection method for a laboratory information system provided by the present invention is described in detail below in conjunction with the accompanying drawings.

[0056] See also Figure 1 , which shows the basic process of a data collection method for a laboratory information system provided by an embodiment of the present invention.

[0057] like Figure 1 As shown, an embodiment of the present invention provides a data collection method for a laboratory information system, which specifically includes:

[0058] S100: Acquire experimental report data of historical samples, wherein the experimental report data includes sample source, experimental purpose, experimental parameters, and experimental analysis, and simultaneously obtain the sample source and experimental purpose of the current sample.

[0059] The laboratory's information management system records the experimental report data of each historical sample, which includes the sample source, experimental purpose, experimental parameters, experimental data, and experimental analysis. Therefore, first obtain the experimental report data of the historical sample from the laboratory's information management system, and at the same time obtain the sample source and experimental purpose of the current sample. This embodiment analyzes the experimental parameters and sampling frequency of the experimental parameters required for the current experiment through the content of the experimental report generated by each sample in the laboratory's information management system within the last 20 days (one sample corresponds to one experimental report).

[0060] S200: Analyze the similarity of the experimental purpose between all the historical samples and the current sample to obtain a reference sample, and determine the experimental parameters of the current sample based on the experimental parameters of the reference sample.

[0061] The experimental purpose in the experimental report clarifies the core issues and research directions of the experiment. For example, when analyzing soil samples, in order to analyze the importance of the experimental parameters of the current soil sample for different experimental purposes such as detecting soil fertility and detecting soil pollution, the experimental parameters of the current soil sample are first needed. The experimental parameters of the soil analyzed with the same experimental purpose are consistent. Therefore, the experimental parameters of the current sample can be determined by the experimental parameters corresponding to the soil sample with a similar experimental purpose to the current experiment.

[0062] Based on the above analysis, this embodiment obtains a reference sample by analyzing the similarity of the experimental purpose between all the historical samples and the current sample, and determines the experimental parameters of the current sample based on the experimental parameters of the reference sample.

[0063] See also Figure 2 , which shows a basic process for determining experimental parameters of a current sample provided by an embodiment of the present invention.

[0064] like Figure 2 As shown, the similarity of the experimental purpose between all the historical samples and the current sample is analyzed to obtain a reference sample, and the experimental parameters of the current sample are determined based on the experimental parameters of the reference sample, including:

[0065] S201: Obtaining the experimental purpose sentence vectors of the historical samples and the current sample.

[0066] The JieBa word segmentation tool in natural language processing is used to segment the experimental purpose sentences of the historical samples and the current sample, and each word in the experimental purpose is converted into a fixed-length word vector through the Word2Vec model. The word vector contains the semantic information of the word, and then the experimental purpose sentence vector is represented by the mean of all word vectors in the experimental purpose sentence. The above technologies are all well-known technologies and will not be repeated here.

[0067] S202: Calculate the similarity of the experimental purpose between the historical sample and the current sample according to the experimental purpose sentence vector.

[0068] Through step S201, the experimental purpose sentence vector corresponding to the experimental purpose of the current sample and the experimental purpose sentence vector corresponding to the experimental purpose of each historical sample are obtained. The similarity between the experimental purpose sentence vectors can be used to represent the similarity between the experimental purpose corresponding to the current sample and the historical sample. Therefore, this embodiment calculates the experimental purpose similarity between the historical sample and the current sample based on the experimental purpose sentence vector, and the calculation formula for the experimental purpose similarity is:

[0069] ;

[0070] In the formula, Indicates The similarity of the experimental purpose between the historical samples and the current sample; Indicates the experimental purpose sentence vector corresponding to the current sample, Indicates The experimental purpose sentence vector corresponding to the historical samples; Represents the dot product symbol; express The module length; express The mold length.

[0071] The cosine similarity between the two experimental purpose sentence vectors actually represented is such that the larger the value, the greater the similarity between the experimental purpose sentence vectors, indicating that the experimental purpose corresponding to the historical sample is more similar to the experimental purpose corresponding to the current sample.

[0072] S203: Setting a similarity threshold of the experimental purpose, and obtaining a reference sample according to the similarity of the experimental purpose.

[0073] Through step S202, the similarity between the experimental purpose corresponding to each historical sample and the current sample can be obtained. , The larger the value, the more consistent the experimental purpose of the historical sample is with the current sample. Therefore, by setting the similarity threshold of the experimental purpose, a reference sample is obtained according to the similarity of the experimental purpose. Specifically, the similarity threshold of the experimental purpose is set. for ,Will Greater than The historical samples are used as reference samples for the current samples.

[0074] Traverse all historical samples and obtain all reference samples of the current sample.

[0075] S204: Acquire the experimental parameters appearing in the experimental reports of all the reference samples to obtain the proposed experimental parameters of the current sample.

[0076] The experimental parameters appearing in the experimental reports of all reference samples are obtained. At this time, each reference sample corresponds to a set of experimental parameters. All experimental parameters that have appeared in all reference samples are taken as the proposed experimental parameters of the current sample.

[0077] S205: Analyze the consistency between any two detection elements of the proposed experimental parameters to obtain the similarity of the experimental parameters.

[0078] Different researchers may use different names for the experimental parameters of samples according to their professional habits. For example, some researchers may call the experimental parameters "soil ecological fertility" as "soil biological fertility", and some researchers may call the experimental parameters "heavy metal content in soil" as "heavy metal content in soil" or "heavy metal level in soil". Therefore, the proposed experimental parameters obtained above may contain experimental parameters with the same detection purpose. These experimental parameters have different names, but the specific detection elements are consistent and are reflected in the experimental report. For example, the detection elements of heavy metal content in soil include lead, cadmium, mercury, and chromium. Therefore, the consistency of the detection elements in the experimental parameters can be used to screen out repeated experimental parameters with the same elements.

[0079] Based on the above analysis, this embodiment first obtains the experimental parameter similarity by analyzing the consistency between the detection elements of any two of the proposed experimental parameters. Further, by analyzing the name similarity of any two of the proposed experimental parameters, and analyzing the element similarity between the detection element sequences corresponding to any two of the proposed experimental parameters, combined with the length of the detection element sequence corresponding to the proposed experimental parameters, the experimental parameter similarity is obtained. The calculation formula for constructing the experimental parameter similarity is:

[0080] ;

[0081] In the formula, Indicates the proposed experimental parameters and proposed experimental parameters Similarity of experimental parameters between Indicates the proposed experimental parameters The corresponding word vector; Indicates the proposed experimental parameters The corresponding word vector; Represents word vector With word vector Calculate cosine similarity; Indicates the proposed experimental parameters The detection element sequence of Indicates the proposed experimental parameters The detection element sequence of Represents a sequence of detection elements With the detection element sequence Calculate Jaccard similarity; Represents a sequence of detection elements The length of the sequence; Represents a sequence of detection elements The length of the sequence; adding 1 is to prevent the denominator from being 0.

[0082] Indicates the proposed experimental parameters Proposed experimental parameters The larger the value, the better the proposed experimental parameters. Proposed experimental parameters The more similar the names are; Indicates the proposed experimental parameters Proposed experimental parameters The corresponding detection element sequence and The similarity of elements between them is important when formulating experimental parameters Proposed experimental parameters The higher the similarity of the detection element sequences and the more consistent the number of detection element sequences, the larger the corresponding value, indicating that the proposed experimental parameters Proposed experimental parameters The corresponding detection element sequence and The more similar they are, the better the experimental parameters are. Proposed experimental parameters The more similar the detected elements are.

[0083] S206: Based on the similarity of the experimental parameters, cluster analysis is performed on the proposed experimental parameters to obtain experimental parameter clusters.

[0084] According to the similarity of the experimental parameters obtained by the above calculation, the proposed experimental parameters are clustered and analyzed, and the proposed experimental parameters with greater similarity are clustered into one category. The DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm is used here. The experimental parameters can be divided into N categories by this algorithm. The similarity of the experimental parameters in each cluster is greater, and the similarity between clusters is smaller.

[0085] S207: extracting the cluster center experimental parameters of the experimental parameter clustering cluster, and determining the experimental parameters of the current sample.

[0086] The cluster center experimental parameters of the experimental parameter clustering cluster are extracted as representative experimental parameters, and the representative experimental parameters are subsequently used as experimental parameters of the current sample.

[0087] S300: Based on the experimental parameters of the reference sample, analyze the occurrence frequency of the experimental parameters of the current sample to obtain the universality of the experimental parameters.

[0088] When an experimental parameter is used multiple times in checking soil samples in an experiment, it means that the universality of this experimental parameter is strong. Therefore, based on the experimental parameters of the reference sample, the frequency of occurrence of the experimental parameters of the current sample is analyzed to obtain the universality of the experimental parameters. The universality calculation formula of the experimental parameters is as follows:

[0089] ;

[0090] In the formula, Indicates the experimental parameters of the current sample universality; represents the total number of experimental parameters in all reference samples; Indicates the experimental parameters of the current sample The number of times it appears in all parameter samples. It should be noted that the total number of experimental parameters in all reference samples includes multiple experimental parameters with different names but the same actual detection elements, and the number is recorded as multiple, for example, "heavy metal content in soil" and "heavy metal level in soil" are recorded as 2 experimental parameters; and the experimental parameters of the current sample This includes multiple experimental parameters with different names but the same detected elements. For example, when counting the number of experimental parameters of "heavy metal content in soil", you are actually counting the number of two experimental parameters: "heavy metal content in soil" and "heavy metal level in soil".

[0091] The larger the value, the better the experimental parameters of the current sample. The greater the frequency of use, the more universal the current experimental parameters are.

[0092] S400: Based on the sample source, analyze the possibility that the current sample and the reference sample are located in the same area to obtain a target sample, analyze the frequency of occurrence of the experimental parameters of the current sample in the experimental analysis of the target sample, and combine the similarity of the experimental purpose between the target sample and the current sample to obtain the attention of the experimental parameters.

[0093] The formation, development and characteristics of soil vary greatly under different climatic conditions. For example, in humid climate zones, researchers may pay more attention to soil drainage and air permeability, because excessive precipitation may cause waterlogging in the soil and affect plant growth; while in arid climate zones, soil moisture content becomes a key parameter. Therefore, researchers pay different attention to the experimental parameters of soil samples in different regions.

[0094] Based on the above analysis, this embodiment analyzes the possibility that the current sample and the reference sample are located in the same area based on the sample source, obtains the target sample, analyzes the frequency of occurrence of the experimental parameters of the current sample in the experimental analysis of the target sample, and combines the similarity of the experimental purpose between the target sample and the current sample to obtain the attention of the experimental parameters.

[0095] See also Figure 3 , which shows the basic process of an experimental parameter attention analysis method provided by an embodiment of the present invention.

[0096] like Figure 3 As shown, based on the sample source, the possibility that the current sample and the reference sample are located in the same region is analyzed to obtain a target sample, and the frequency of occurrence of the experimental parameters of the current sample in the experimental analysis of the target sample is analyzed, and the similarity of the experimental purpose between the target sample and the current sample is combined to obtain the attention of the experimental parameters, including:

[0097] S401: Based on the sample sources of the current sample and the reference sample, obtain the regional locations of the current sample and the reference sample.

[0098] In the sample experimental report, the sample source column will mark the specific information of the sample, including the detailed location information of the sample. Therefore, based on the sample sources of the current sample and the reference sample, the regional locations of the current sample and the reference sample are obtained. The detailed location information of the sample in the sample source of the experimental report can be obtained, and the attribute information of the location can be obtained through the geographic information system software, including latitude and longitude and altitude.

[0099] S402: Analyze the longitude and latitude distance relationship and the altitude relationship between the regional locations of the current sample and the reference sample to obtain the possibility that the current sample and the reference sample are located in the same region.

[0100] The regional locations of the current sample and the reference sample are represented by latitude and longitude coordinates and altitude. A reference sample that is closer to the current sample location and has a smaller altitude difference indicates that the reference sample and the current sample are located in the same region.

[0101] Therefore, this embodiment analyzes the longitude and latitude distance relationship and altitude relationship between the regional locations of the current sample and the reference sample to obtain the possibility that the current sample and the reference sample are located in the same region. The possibility calculation formula is:

[0102] ;

[0103] In the formula, Indicates The probability that the reference sample is located in the same region as the current sample; Indicates the latitude and longitude of the current sample location; Indicates The latitude and longitude of the area where the reference samples are located; It means to calculate the distance between any two points on the earth by the longitude and latitude between the two points; Indicates the altitude of the current sample location; Indicates The altitude of the location of the reference samples; Indicated by natural constant An exponential function with base .

[0104] Indicates the longitude and latitude distance relationship between the current sample and the reference sample. The smaller the value, the closer the longitude and latitude distance between the reference sample and the current sample, and the greater the possibility that the corresponding reference sample and the current sample are located in the same area. Indicates the altitude relationship between the regional locations of the current sample and the reference sample. The smaller the difference, the closer the altitude of the previous sample is to the location of the reference sample, and the greater the possibility that the corresponding reference sample and the current sample are located in the same area.

[0105] S403: Setting a possibility threshold, and obtaining a target sample according to the possibility.

[0106] The probability that the current sample is located in the same region as the reference sample The larger the value, the The greater the possibility that the reference sample is in the same area as the current sample location, the greater the probability that the probability threshold is set. is 0.5, take Greater than The reference sample at that time is taken as the target sample, and the target sample is represented as being located in the same area as the current sample.

[0107] Traverse all reference samples to obtain all target samples located in the same area as the current sample.

[0108] In the experimental report, the higher the frequency of an experimental parameter appearing in the experimental analysis, it often means that the researchers have given more attention and consideration to this experimental parameter in various links such as experimental design, data collection and result interpretation. That is, this experimental parameter may have an important role and research significance in the analysis of samples. Therefore, the frequency of the experimental parameter appearing in the experimental analysis can be used to show the researchers' attention to the experimental parameter.

[0109] However, some experimental parameters may include multiple specific detection elements, and the experimental analysis may focus on the data of each detection element. Therefore, it is not possible to calculate only based on the frequency of occurrence of the experimental parameters, but also necessary to consider the performance of the detection elements included in the experimental parameters in the experimental analysis. The specific steps of calculating the frequency of occurrence of the experimental parameters include S404 to S408.

[0110] S404: Obtain a word segmentation sequence in the experimental analysis of the target sample.

[0111] The experimental analysis part of the experimental report of each target sample is obtained, and the JieBa word segmentation tool is used to segment the experimental analysis content. At this time, the word segmentation sequence corresponding to each target sample can be obtained.

[0112] S405: Analyze the segmentation similarity between the segmentation sequence and the experimental parameters of the current sample.

[0113] Calculate the experimental parameters for the current sample With The similarity of each word in the word sequence corresponding to the target sample

[0114] ;

[0115] In the formula, Indicates the experimental parameters of the current sample With The first word in the word sequence corresponding to the target sample Similarity of the word segments; Indicates the experimental parameters of the current sample participle of; Indicates The first word in the word sequence corresponding to the target sample participle; Participle and Compute cosine similarity.

[0116] Traverse the word segmentation sequences corresponding to all target samples to obtain the word segmentation similarity between all the word segmentations in all word segmentation sequences and the word segmentations of all experimental parameters of the current sample.

[0117] S406: Setting a segmentation similarity threshold, and obtaining experimental parameter segmentations in the experimental analysis of the target sample according to the segmentation similarity.

[0118] With the experimental parameters of the current sample With Take the target sample as an example. Set the word segmentation similarity threshold is 0.5, and the word similarity Greater than the word segmentation similarity threshold The word segmentation is used as the experimental parameter of the current sample The consistent participle is the experimental parameter participle. All experimental parameters and the detection elements contained in the experimental parameters can be found in the experimental analysis of the target sample. For example, [heavy metal content in soil] is expressed as a participle, which includes lead, cadmium, mercury, and chromium as detection elements.

[0119] S407: Analyze a first ratio relationship between the number of times the experimental parameter segmentation appears in the experimental analysis of the target sample and the total number of all experimental parameter segmentations in the experimental analysis of the target sample, and analyze a second ratio relationship between the mean number of times all detection elements corresponding to the experimental parameter segmentation appear in the experimental analysis of the target sample and the total number of all experimental parameter segmentations in the experimental analysis of the target sample.

[0120] With the experimental parameters of the current sample With Analyze the experimental parameters The participle in The number of times the target sample appears With the said The total number of experimental parameter segmentations in the experimental analysis of target samples The first ratio relationship between , and analyzing the experimental parameters All the detection elements corresponding to the word segmentation are in the The average number of times the target samples appear in the experimental analysis ( Indicates experimental parameters The corresponding participle The detection element is The number of occurrences in the target sample) is the same as the The total number of experimental parameter segmentations in the experimental analysis of target samples The second ratio relationship .

[0121] S408: Combining the first ratio relationship and the second ratio relationship, obtaining the occurrence frequency of the experimental parameter of the current sample in the experimental analysis of the target sample.

[0122] With the experimental parameters of the current sample With Take the target sample as an example. At this time, for the experimental parameters The participle in The frequency of occurrence of target samples in the experimental analysis can be expressed as the experimental parameter The frequency of occurrence of participles accounts for The proportion of the frequency of all experimental parameters in the experimental analysis of the target samples; In the The frequency of occurrence in the experimental analysis of a target sample may also be the frequency of occurrence of the detection element contained in the experimental parameter; therefore, the overall experimental parameter is represented by the sum of the frequencies of the two. In the The frequency of occurrence in the experimental analysis of target samples is calculated as follows:

[0123] ;

[0124] In the formula, Indicates experimental parameters In the The frequency of occurrence of target samples in the experimental analysis; Indicates The total number of all experimental parameter segmentations in the experimental analysis of the target sample (including the specific detection elements of each experimental parameter); Indicates experimental parameters The participle in The number of times a target sample appears in the experimental analysis; Indicates experimental parameters The corresponding participle The detection element is The number of times a target sample appears in the experimental analysis; Indicates experimental parameters The number of detection elements corresponding to the word segmentation.

[0125] Expressed as experimental parameters The participle in The frequency of occurrence of the target sample in the experimental analysis; Indicates experimental parameters The The detection element is The frequency of occurrence of the target sample in the experimental analysis; Expressed as experimental parameters All detected elements in The mean of the frequency of occurrence in the experimental analysis of target samples; The closer to 1, the better the experimental parameters. In the The frequency of occurrence in the experimental analysis of target samples is high.

[0126] S409: Obtain the attention degree of the experimental parameter according to the appearance frequency of the experimental parameter of the current sample in the experimental analysis of the target sample and the similarity of the experimental purpose between the target sample and the current sample.

[0127] The frequency of occurrence of the experimental parameters of the current sample in the experimental analysis of the target sample is weighted, and the weight coefficient is the similarity of the experimental purpose between the target sample and the current sample. All the target samples are traversed to find the average value to obtain the attention of the experimental parameters. The calculation formula for the attention of the experimental parameters is:

[0128] ;

[0129] In the formula, Indicates the experimental parameters of the current sample 's attention; Represents the current sample and the The similarity of the experimental purpose of the target samples (obtained in step S202); Expressed as experimental parameters In the The frequency of occurrence of target samples in the experimental analysis; Indicates the total number of target samples corresponding to the current sample.

[0130] Expressed as experimental parameters The mean frequency of all target samples in the experimental analysis. The larger the value, the better the experimental parameters. The higher the attention.

[0131] Finally, we can get the researchers’ attention to all experimental parameters of the current sample. .

[0132] S500: Obtaining the importance of the experimental parameters according to the prevalence and attention of the experimental parameters.

[0133] With the experimental parameters of the current sample . Experimental parameters for the current sample The more common the experiment is and the more researchers are careful about the experimental parameters, The higher the attention, the more important the experimental parameter is to the current sample.

[0134] At this time, according to the prevalence and attention of the experimental parameters, the importance of the experimental parameters is obtained as follows:

[0135] ;

[0136] In the formula, Indicates experimental parameters the importance of Indicates experimental parameters universality; Indicates experimental parameters 's attention; represents the linear normalization function.

[0137] The larger the experimental parameter The higher the prevalence, The larger the value, the more researchers are interested in the experimental parameters. The higher the attention, The larger the value, the more important the experimental parameter is to the current sample.

[0138] S600: Setting a sampling frequency of the experimental parameter according to the importance of the experimental parameter.

[0139] According to the importance of the experimental parameters, the sampling frequency of the experimental parameters is set, including: sorting the importance of the experimental parameters from large to small; taking the first The experimental parameters are used as the actual experimental parameters of the current sample. The value of can be 5; when the importance of the experimental parameter to the current sample is greater, the sampling frequency of the corresponding experimental parameter in the current sample is greater, so the sampling frequency of the actual experimental parameter is set to times the experimental parameter's attention level, rounded up to an integer value, The value can be 10.

[0140] Based on the same inventive concept as the above method, this embodiment also provides a data acquisition system for a laboratory information system.

[0141] See also Figure 4 , which shows the basic composition of a data acquisition system for a laboratory information system provided by an embodiment of the present invention.

[0142] like Figure 4 As shown, a data acquisition system for a laboratory information system includes: a memory 10 and a processor 20, wherein:

[0143] A memory 10, used for storing program codes;

[0144] The processor 20 is used to read the program code stored in the memory 10, and execute to obtain the experimental report data of the historical samples, the experimental report data includes the sample source, experimental purpose, experimental parameters, experimental analysis, and obtain the sample source and experimental purpose of the current sample; analyze the similarity of the experimental purpose between all historical samples and the current sample to obtain a reference sample, and determine the experimental parameters of the current sample based on the experimental parameters of the reference sample; analyze the frequency of occurrence of the experimental parameters of the current sample based on the experimental parameters of the reference sample to obtain the universality of the experimental parameters; based on the sample source, analyze the possibility that the current sample and the reference sample are located in the same area to obtain the target sample, analyze the frequency of occurrence of the experimental parameters of the current sample in the experimental analysis of the target sample, and obtain the attention of the experimental parameters in combination with the similarity of the experimental purpose between the target sample and the current sample; obtain the importance of the experimental parameters according to the universality and attention of the experimental parameters; set the sampling frequency of the experimental parameters according to the importance of the experimental parameters.

[0145] Furthermore, the processor 20 includes an experiment report acquisition module 21, an experiment parameter determination module 22, an experiment parameter analysis module 23, and a sampling frequency determination module 24. Among them:

[0146] The experimental report acquisition module 21 is used to obtain the experimental report data of the historical samples, the experimental report data includes the sample source, experimental purpose, experimental parameters, experimental analysis, and the sample source and experimental purpose of the current sample;

[0147] The experimental parameter determination module 22 is used to analyze the similarity of the experimental purpose between all the historical samples and the current sample, obtain a reference sample, and determine the experimental parameters of the current sample based on the experimental parameters of the reference sample;

[0148] The experimental parameter analysis module 23 is used to analyze the occurrence frequency of the experimental parameters of the current sample based on the experimental parameters of the reference sample to obtain the universality of the experimental parameters; and based on the source of the sample, analyze the possibility that the current sample and the reference sample are located in the same area to obtain the target sample, analyze the occurrence frequency of the experimental parameters of the current sample in the experimental analysis of the target sample, and obtain the attention of the experimental parameters in combination with the similarity of the experimental purpose between the target sample and the current sample; and obtain the importance of the experimental parameters according to the universality and attention of the experimental parameters;

[0149] The sampling frequency determination module 24 is used to set the sampling frequency of the experimental parameter according to the importance of the experimental parameter.

[0150] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0151] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A data collection method for a laboratory information system, characterized in that: The method comprises: Obtaining the experimental report data of historical samples, the experimental report data including the sample source, experimental purpose, experimental parameters, and experimental analysis, and obtaining the sample source and experimental purpose of the current sample; Analyze the similarity of the experimental purpose between all the historical samples and the current sample to obtain a reference sample, and determine the experimental parameters of the current sample based on the experimental parameters of the reference sample; Based on the experimental parameters of the reference sample, analyzing the occurrence frequency of the experimental parameters of the current sample to obtain the universality of the experimental parameters; Based on the sample source, the possibility that the current sample and the reference sample are located in the same region is analyzed to obtain a target sample, and the frequency of occurrence of the experimental parameters of the current sample in the experimental analysis of the target sample is analyzed, and the attention degree of the experimental parameters is obtained by combining the similarity of the experimental purpose between the target sample and the current sample; According to the prevalence and attention of the experimental parameters, the importance of the experimental parameters is obtained; According to the importance of the experimental parameters, the sampling frequency of the experimental parameters is set; Determining the experimental parameters of the current sample based on the experimental parameters of the reference sample includes: Obtaining the experimental parameters appearing in the experimental reports of all the reference samples to obtain the proposed experimental parameters of the current sample; Analyze the consistency between any two detection elements of the proposed experimental parameters to obtain the similarity of the experimental parameters; Based on the similarity of the experimental parameters, cluster analysis is performed on the proposed experimental parameters to obtain experimental parameter clusters; Extracting the cluster center experimental parameters of the experimental parameter clustering cluster to determine the experimental parameters of the current sample; The universal calculation formula for experimental parameters is as follows: In the formula, Indicates the experimental parameters of the current sample universality; represents the total number of experimental parameters in all reference samples; Indicates the experimental parameters of the current sample The number of times it appears in all parameter samples; A weight is set for the frequency of occurrence of the experimental parameter of the current sample in the experimental analysis of the target sample, where the weight coefficient is the similarity of the experimental purpose between the target sample and the current sample, and the average is calculated by traversing all the target samples to obtain the attention degree of the experimental parameter; According to the prevalence and attention of the experimental parameters, the importance of the experimental parameters is obtained as follows: In the formula, Indicates experimental parameters the importance of Indicates experimental parameters universality; Indicates experimental parameters 's attention; represents the linear normalization function.

2. The data collection method for a laboratory information system according to claim 1, characterized in that: Analyze the similarity of the experimental purpose between all the historical samples and the current sample to obtain a reference sample, including: Obtaining the experimental purpose sentence vectors of the historical sample and the current sample; Calculating the similarity of the experimental purpose between the historical sample and the current sample according to the experimental purpose sentence vector; A similarity threshold for the experimental purpose is set, and a reference sample is obtained according to the similarity for the experimental purpose.

3. The data collection method for laboratory information system according to claim 1, characterized in that: Analyze the consistency between any two detection elements of the proposed experimental parameters to obtain the similarity of the experimental parameters, including: The similarity of the names of any two of the proposed experimental parameters is analyzed, and the similarity of the elements between the detection element sequences corresponding to any two of the proposed experimental parameters is analyzed, and the similarity of the experimental parameters is obtained in combination with the length of the detection element sequence corresponding to the proposed experimental parameters.

4. The data collection method for a laboratory information system according to claim 1, characterized in that: Based on the source of the sample, analyzing the possibility that the current sample and the reference sample are located in the same region to obtain a target sample includes: Based on the sample sources of the current sample and the reference sample, obtaining the regional locations of the current sample and the reference sample; Analyze the longitude and latitude distance relationship and the altitude relationship between the regional locations of the current sample and the reference sample to obtain the possibility that the current sample and the reference sample are located in the same region; A possibility threshold is set, and a target sample is obtained based on the possibility.

5. The data collection method for a laboratory information system according to claim 1 or 4, characterized in that: Analyzing the occurrence frequency of the experimental parameters of the current sample in the experimental analysis of the target sample includes: Obtaining a word segmentation sequence in an experimental analysis of the target sample; Analyzing the segmentation similarity between the segmentation sequence and the experimental parameters of the current sample; Setting a segmentation similarity threshold, and obtaining the experimental parameter segmentation in the experimental analysis of the target sample according to the segmentation similarity; Analyzing a first ratio relationship between the number of times the experimental parameter segmentation appears in the experimental analysis of the target sample and the total number of all experimental parameter segmentations in the experimental analysis of the target sample, and analyzing a second ratio relationship between the mean number of times all detection elements corresponding to the experimental parameter segmentation appear in the experimental analysis of the target sample and the total number of all experimental parameter segmentations in the experimental analysis of the target sample; The first ratio relationship and the second ratio relationship are combined to obtain the occurrence frequency of the experimental parameter of the current sample in the experimental analysis of the target sample.

6. The data collection method for laboratory information system according to claim 1, characterized in that: According to the importance of the experimental parameters, the sampling frequency of the experimental parameters is set, including: Sort the experimental parameters from most important to least important; Before The experimental parameters are used as the actual experimental parameters of the current sample; Set the sampling frequency of the actual experimental parameters to The attention level of the experimental parameter is rounded up to an integer value.

7. A data acquisition system for a laboratory information system, characterized in that: The system comprises: a memory and a processor, wherein: The memory is used to store program codes; The processor is configured to read the program code stored in the memory and execute the method according to any one of claims 1 to 6.

8. The data acquisition system for laboratory information system according to claim 7, characterized in that: The processor comprises: The experimental report acquisition module is used to obtain the experimental report data of historical samples, wherein the experimental report data includes the sample source, experimental purpose, experimental parameters, and experimental analysis, and simultaneously obtain the sample source and experimental purpose of the current sample; An experimental parameter determination module, used to analyze the similarity of the experimental purpose between all the historical samples and the current sample, obtain a reference sample, and determine the experimental parameters of the current sample based on the experimental parameters of the reference sample; The experimental parameter analysis module is used to analyze the occurrence frequency of the experimental parameters of the current sample based on the experimental parameters of the reference sample to obtain the universality of the experimental parameters; and based on the source of the sample, analyze the possibility that the current sample and the reference sample are located in the same area to obtain the target sample, analyze the occurrence frequency of the experimental parameters of the current sample in the experimental analysis of the target sample, and obtain the attention of the experimental parameters in combination with the similarity of the experimental purpose between the target sample and the current sample; and obtain the importance of the experimental parameters according to the universality and attention of the experimental parameters; A sampling frequency determination module, used to set the sampling frequency of the experimental parameters according to the importance of the experimental parameters; Determining the experimental parameters of the current sample based on the experimental parameters of the reference sample includes: Obtaining the experimental parameters appearing in the experimental reports of all the reference samples to obtain the proposed experimental parameters of the current sample; Analyze the consistency between any two detection elements of the proposed experimental parameters to obtain the similarity of the experimental parameters; Based on the similarity of the experimental parameters, cluster analysis is performed on the proposed experimental parameters to obtain experimental parameter clusters; Extracting the cluster center experimental parameters of the experimental parameter clustering cluster to determine the experimental parameters of the current sample; The universal calculation formula for experimental parameters is as follows: In the formula, Indicates the experimental parameters of the current sample universality; represents the total number of experimental parameters in all reference samples; Indicates the experimental parameters of the current sample The number of times it appears in all parameter samples; A weight is set for the frequency of occurrence of the experimental parameter of the current sample in the experimental analysis of the target sample, where the weight coefficient is the similarity of the experimental purpose between the target sample and the current sample, and the average is calculated by traversing all the target samples to obtain the attention degree of the experimental parameter; According to the prevalence and attention of the experimental parameters, the importance of the experimental parameters is obtained as follows: In the formula, Indicates experimental parameters the importance of Indicates experimental parameters universality; Indicates experimental parameters 's attention; represents the linear normalization function.

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