CN112037915A - Enterprise employee health data analysis method, device, equipment and storage medium - Google Patents
Enterprise employee health data analysis method, device, equipment and storage medium Download PDFInfo
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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Abstract
The invention relates to the field of big data, and discloses a method, a device, equipment and a storage medium for analyzing health data of enterprise employees, which are applied to the field of intelligent medical treatment and are used for avoiding screening a large amount of data when the health data of the enterprise employees are analyzed, so that the analysis efficiency of the health data of the enterprise employees is improved. The method for analyzing the health data of the enterprise employees comprises the following steps: segmenting and rejecting employee information data in sequence by using a preset segmentation function, a preset rejection function and a disease label to obtain residual information, and determining abnormal disease data in the employee information data in the residual information; generating a basic display table by adopting the attribute labels in the employee information data and the abnormal disease labels in the abnormal disease data; performing visual rendering on the basic display table to generate a target display set; and acquiring estimated risk data corresponding to the abnormal disease data of the enterprise staff and a corresponding risk solution in the target display set, and determining the health analysis result of the enterprise staff.
Description
Technical Field
The invention relates to the field of big data, in particular to a method, a device, equipment and a storage medium for analyzing health data of enterprise employees.
Background
Enterprises generally neglect the health degree of employees while pursuing high profits, and the excessive working pressure is in pace with the psychological and physical health of the employees. In the prior art, there is a health monitoring system for enterprise employees, which can obtain current health evaluation reports of the employees by analyzing health data of the enterprise employees.
However, when the health data of the enterprise employees is analyzed by using the technology, the acquired employee data is screened completely, and the enterprise employee data is analyzed one by one, so that the analysis efficiency of the enterprise employee health monitoring system for analyzing the health data of the enterprise employees is low due to a large amount of data screening.
Disclosure of Invention
The invention provides an analysis method, an analysis device, analysis equipment and a storage medium for health data of enterprise employees, which are used for avoiding screening a large amount of data when the health data of the enterprise employees are analyzed, and improving the analysis efficiency of the health data of the enterprise employees.
The invention provides a method for analyzing health data of enterprise employees in a first aspect, which comprises the following steps: acquiring employee information data and disease labels of enterprise employees, segmenting and rejecting the employee information data in sequence by using a preset segmentation function, a preset rejection function and the disease labels to obtain residual information, and determining abnormal disease data in the employee information data in the residual information; generating a basic display table by adopting the attribute labels in the employee information data and the abnormal disease labels in the abnormal disease data, wherein the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data; performing visual rendering on the basic display table to generate a target display set, wherein the target display set comprises a line graph, a bar graph, a scatter diagram, a K line graph and a box graph which are generated on the basis of the basic display table; and acquiring estimated risk data corresponding to the abnormal disease data of the enterprise staff and a corresponding risk solution in the target display set, combining the estimated risk data corresponding to the enterprise staff and the risk solution, and determining the health analysis result of the enterprise staff.
Optionally, in a first implementation manner of the first aspect of the present invention, the obtaining of employee information data and a disease label of an enterprise employee is performed, the employee information data is segmented and removed in sequence by using a preset segmentation function, a preset removal function and the disease label to obtain remaining information, determining abnormal disease data in the employee information data in the remaining information includes obtaining employee information data of the enterprise employee, and searching for required information data to be detected in the employee information data through a regular expression; acquiring a disease label, and segmenting the information data to be detected by using a preset segmentation function and the disease label to obtain segmentation information, wherein the segmentation information is used for describing the disease information of the enterprise staff about the corresponding disease label; rejecting the segmented information with preset interference corpora by using a preset rejection function to obtain residual information; extracting disease index data corresponding to the disease label from the residual information through a preset calling function; comparing the disease index data with standard range data, and determining the disease index data as abnormal data when the disease index data is not in the standard range data; and determining a disease label corresponding to the abnormal data as an abnormal disease label by using a preset corpus rule, and taking employee information data corresponding to the abnormal disease label as abnormal disease data.
Optionally, in a second implementation manner of the first aspect of the present invention, the generating a basic display table by using the attribute tag in the employee information data and the abnormal disease tag in the abnormal disease data, where the basic display table is used to indicate a relationship between the employee information data and the abnormal disease data includes: acquiring an attribute tag in the employee information data, wherein the attribute tag is used for indicating the property of the employee information data; calculating a Cartesian product between the attribute tag and the abnormal disease tag to obtain a tag combination; establishing an initial display table based on the label combination, and filling employee information data and abnormal disease data corresponding to the label combination into the initial display table by using a preset extraction function to obtain a basic display table, wherein labels in the label combination are column labels and row labels of the initial display table respectively, and the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data.
Optionally, in a third implementation manner of the first aspect of the present invention, the visually rendering the basic display table to generate a target display set, where the target display set includes a line graph, a bar graph, a scatter graph, a K-line graph, and a box graph generated based on the basic display table includes: inputting the basic display form into a preset data table to obtain a basic data table, and completing the input of employee information data and abnormal disease data of enterprise employees; and respectively converting the basic data table into a line graph, a bar graph, a scatter diagram, a K line graph and a box graph by using a preset vector conversion function to generate a target display set.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the obtaining, in the target display set, pre-estimated risk data corresponding to the abnormal disease data of the enterprise employee and a corresponding risk solution, merging the pre-estimated risk data corresponding to the enterprise employee and the risk solution, and determining a health analysis result of the enterprise employee includes: extracting abnormal disease data corresponding to the enterprise employees from the target display set to obtain target disease data; calculating the basic similarity between the target disease data and the standard disease data in a preset rule solution library; when the basic similarity is larger than or equal to a standard threshold, acquiring preset risk data corresponding to the standard disease data and a corresponding preset solution, and taking the preset risk data and the corresponding preset solution as estimated risk data and a risk solution corresponding to the enterprise staff; and merging the estimated risk data corresponding to the enterprise staff and the risk solution, and determining the health analysis result of the enterprise staff.
Optionally, in a fifth implementation manner of the first aspect of the present invention, after the generating a basic display table by using the attribute tag in the employee information data and the abnormal disease tag in the abnormal disease data, and after the generating the basic display table is used to indicate a relationship between the employee information data and the abnormal disease data, performing a visual rendering on the basic display table to generate a target display set, where the target display set includes a line graph, a bar graph, a scatter graph, a K-line graph, and a box graph that are generated based on the basic display table, the method further includes: acquiring the update information data of the enterprise staff, integrating the staff information data and the update information data by using a preset integration function, generating an information data comparison graph of the enterprise staff, and storing the information data comparison graph into a target display set.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the acquiring update information data of the enterprise employee, integrating the employee information data and the update information data by using a preset integration function, generating an information data comparison graph of the enterprise employee, and storing the information data comparison graph into a target display set includes: acquiring update information data of the enterprise staff, and storing the update information data into a preset database; acquiring an entry time in the employee information data and an update time in the update information data, and calculating the entry time and the update time to obtain an interval period between the entry time and the update time; and integrating the employee information data and the updated information data by adopting a preset integration function, generating an information data comparison graph of the enterprise employees in the interval time period, and storing the information data comparison graph into a target display set.
The invention provides a device for analyzing health data of enterprise employees, comprising: the system comprises an acquisition module, a classification module and a processing module, wherein the acquisition module is used for acquiring employee information data and disease labels of enterprise employees, segmenting and removing the employee information data in sequence by using a preset segmentation function, a preset removal function and the disease labels to obtain residual information, and determining abnormal disease data in the employee information data in the residual information; the generating module is used for generating a basic display table by adopting the attribute labels in the employee information data and the abnormal disease labels in the abnormal disease data, and the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data; the display module is used for performing visual rendering on the basic display table to generate a target display set, and the target display set comprises a line graph, a bar graph, a scatter diagram, a K line graph and a box graph which are generated on the basis of the basic display table; and the determining module is used for acquiring the estimated risk data corresponding to the abnormal disease data of the enterprise staff and the corresponding risk solution in the target display set, combining the estimated risk data corresponding to the enterprise staff and the risk solution and determining the health analysis result of the enterprise staff.
Optionally, in a first implementation manner of the second aspect of the present invention, the obtaining module is specifically configured to: acquiring employee information data of enterprise employees, and searching required information data to be detected in the employee information data through a regular expression; acquiring a disease label, and segmenting the information data to be detected by using a preset segmentation function and the disease label to obtain segmentation information, wherein the segmentation information is used for describing the disease information of the enterprise staff about the corresponding disease label; rejecting the segmented information with preset interference corpora by using a preset rejection function to obtain residual information; extracting disease index data corresponding to the disease label from the residual information through a preset calling function; comparing the disease index data with standard range data, and determining the disease index data as abnormal data when the disease index data is not in the standard range data; and determining a disease label corresponding to the abnormal data as an abnormal disease label by using a preset corpus rule, and taking employee information data corresponding to the abnormal disease label as abnormal disease data.
Optionally, in a second implementation manner of the second aspect of the present invention, the generating module is specifically configured to: acquiring an attribute tag in the employee information data, wherein the attribute tag is used for indicating the property of the employee information data; calculating a Cartesian product between the attribute tag and the abnormal disease tag to obtain a tag combination; establishing an initial display table based on the label combination, and filling employee information data and abnormal disease data corresponding to the label combination into the initial display table by using a preset extraction function to obtain a basic display table, wherein labels in the label combination are column labels and row labels of the initial display table respectively, and the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data.
Optionally, in a third implementation manner of the second aspect of the present invention, the display module is specifically configured to: inputting the basic display form into a preset data table to obtain a basic data table, and completing the input of employee information data and abnormal disease data of enterprise employees; and respectively converting the basic data table into a line graph, a bar graph, a scatter diagram, a K line graph and a box graph by using a preset vector conversion function to generate a target display set.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the determining module is specifically configured to: extracting abnormal disease data corresponding to the enterprise employees from the target display set to obtain target disease data; calculating the basic similarity between the target disease data and the standard disease data in a preset rule solution library; when the basic similarity is larger than or equal to a standard threshold, acquiring preset risk data corresponding to the standard disease data and a corresponding preset solution, and taking the preset risk data and the corresponding preset solution as estimated risk data and a risk solution corresponding to the enterprise staff; and merging the estimated risk data corresponding to the enterprise staff and the risk solution, and determining the health analysis result of the enterprise staff.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the apparatus for analyzing health data of an employee of an enterprise further includes: and the integration module is used for acquiring the update information data of the enterprise staff, integrating the staff information data and the update information data by using a preset integration function, generating an information data comparison graph of the enterprise staff, and storing the information data comparison graph into a target display set.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the integration module is specifically configured to: acquiring update information data of the enterprise staff, and storing the update information data into a preset database; acquiring an entry time in the employee information data and an update time in the update information data, and calculating the entry time and the update time to obtain an interval period between the entry time and the update time; and integrating the employee information data and the updated information data by adopting a preset integration function, generating an information data comparison graph of the enterprise employees in the interval time period, and storing the information data comparison graph into a target display set.
A third aspect of the present invention provides an apparatus for analyzing health data of an employee of an enterprise, comprising: a memory and at least one processor, the memory having instructions stored therein; the at least one processor calls the instructions in the memory to cause the analysis device of the health data of the enterprise employee to execute the analysis method of the health data of the enterprise employee.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which when run on a computer, cause the computer to perform the above-mentioned method for analyzing health data of an employee of an enterprise.
According to the technical scheme provided by the invention, employee information data and disease labels of enterprise employees are obtained, the employee information data are segmented and eliminated in sequence by utilizing a preset segmentation function, a preset elimination function and the disease labels to obtain residual information, and abnormal disease data in the employee information data are determined in the residual information; generating a basic display table by adopting the attribute labels in the employee information data and the abnormal disease labels in the abnormal disease data, wherein the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data; performing visual rendering on the basic display table to generate a target display set, wherein the target display set comprises a line graph, a bar graph, a scatter diagram, a K line graph and a box graph which are generated on the basis of the basic display table; and acquiring estimated risk data corresponding to the abnormal disease data of the enterprise staff and a corresponding risk solution in the target display set, combining the estimated risk data corresponding to the enterprise staff and the risk solution, and determining the health analysis result of the enterprise staff. According to the embodiment of the invention, the abnormal disease data of the enterprise staff is obtained by segmenting and eliminating the staff information data of the enterprise staff, then the basic display table is generated by utilizing the attribute labels and the abnormal disease labels of the enterprise staff, the basic display table is visually rendered, the target display set of the abnormal disease data of the enterprise staff is displayed in a multi-dimensional mode, and finally the health analysis result of the enterprise staff is determined based on the target display set.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a method for analyzing health data of an employee of an enterprise according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of another embodiment of a method for analyzing health data of an employee of an enterprise according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an embodiment of an apparatus for analyzing health data of employees of an enterprise according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of another embodiment of an apparatus for analyzing health data of employees of a business enterprise according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an embodiment of an apparatus for analyzing health data of an employee of an enterprise according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides an analysis method, an analysis device, analysis equipment and a storage medium for health data of enterprise employees, wherein the abnormal disease data of the enterprise employees are obtained by segmenting and eliminating employee information data of the enterprise employees, then a basic display table is generated by utilizing attribute labels and the abnormal disease labels of the enterprise employees, the basic display table is visually rendered, a target display set of the abnormal disease data of the enterprise employees is displayed in a multi-dimensional mode, and finally health analysis results of the enterprise employees are determined based on the target display set.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For convenience of understanding, a specific flow of an embodiment of the present invention is described below, and referring to fig. 1, an embodiment of the method for analyzing health data of enterprise employees according to an embodiment of the present invention includes:
101. acquiring employee information data and disease labels of enterprise employees, segmenting and rejecting the employee information data in sequence by using a preset segmentation function, a preset rejection function and the disease labels to obtain residual information, and determining abnormal disease data in the employee information data in the residual information;
it is to be understood that the execution subject of the present invention may be an analysis apparatus for health data of an employee of an enterprise, and may also be a terminal or a server, which is not limited herein. The embodiment of the present invention is described by taking a server as an execution subject.
Under the situation of rapid development of economy, part of enterprises generally ignore the health degree of enterprise employees while pursuing high profits of the enterprises, and the excessive working pressure is eating the psychological and physical health of the enterprise employees step by step, so a system for monitoring the health of the enterprise employees is needed. When monitoring the health of the enterprise employee, firstly, enterprise employee information data needs to be collected, wherein the enterprise employee information data comprises basic data describing the enterprise employee such as the name, age, sex, position, post, performance, physical examination time and the like of the enterprise employee. The disease label is a disease item for evaluating the health of the staff of the enterprise, and the disease label can be: leukemia label, stomach cancer label, thrombus label, diabetes label, etc., in addition, the number of disease label is at least one, and the number of disease label is not limited in this application, it is further explained that the employee information data includes each disease label and detection information data describing the disease label, and the disease information data includes information data such as disease meaning, concept explanation, formation reason, chief symptom, preventive measure, treatment method, health management advice, etc., such as: the employee A of the enterprise obtains the gastric cancer (disease), which is the precancerous gastric cancer and has the etiology and symptoms of the gastric cancer, corresponding preventive measures, treatment methods and the like.
It should be noted that there is detection information description of a disease corresponding to a disease label in employee information data of an enterprise employee, but all diseases are not abnormal in a plurality of detection information descriptions, so when the server performs health analysis on the enterprise employee, the server first performs screening processing on the employee information data, and then determines abnormal disease data of the enterprise employee.
102. Generating a basic display table by adopting the attribute labels in the employee information data and the abnormal disease labels in the abnormal disease data, wherein the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data;
when the server displays abnormal disease data of enterprise employees, a basic display table is firstly generated and used for indicating the relationship between employee information data and the abnormal disease data, and the basic display table is the basis for generating the multi-dimensional abnormal disease data of the enterprise employees. It should be noted that the number of the basic presentation tables is at least one, wherein the column label and the row label in each basic presentation table are different.
103. Performing visual rendering on the basic display table to generate a target display set, wherein the target display set comprises a line graph, a bar graph, a scatter diagram, a K line graph and a box diagram which are generated on the basis of the basic display table;
after the server obtains the basic display form, it needs to perform visual rendering on the basic display form, that is, the server generates charts or graphs with different display forms by processing the basic display form. The processing realizes the multi-dimensional display of the data, and can enable enterprise employees to observe the relationship between employee information data and abnormal disease data more intuitively.
104. And acquiring estimated risk data corresponding to the abnormal disease data of the enterprise staff and a corresponding risk solution in the target display set, combining the estimated risk data corresponding to the enterprise staff and the risk solution, and determining the health analysis result of the enterprise staff.
After the abnormal disease data of the enterprise staff are clarified, the server can inquire a corresponding disease solution in a preset rule solution library, and provide a corresponding solution of the enterprise staff and a health analysis result of the enterprise staff.
According to the embodiment of the invention, the abnormal disease data of the enterprise staff is obtained by segmenting and eliminating the staff information data of the enterprise staff, then the basic display table is generated by utilizing the attribute labels and the abnormal disease labels of the enterprise staff, the basic display table is visually rendered, the target display set of the abnormal disease data of the enterprise staff is displayed in a multi-dimensional mode, and finally the health analysis result of the enterprise staff is determined based on the target display set.
Referring to fig. 2, another embodiment of the method for analyzing health data of an employee of an enterprise according to the embodiment of the present invention includes:
201. acquiring employee information data and disease labels of enterprise employees, segmenting and rejecting the employee information data in sequence by using a preset segmentation function, a preset rejection function and the disease labels to obtain residual information, and determining abnormal disease data in the employee information data in the residual information;
specifically, the server firstly obtains employee information data of enterprise employees, and searches the needed information data to be detected in the employee information data through a regular expression; secondly, the server acquires a disease label, and segments the information data to be detected by using a preset segmentation function and the disease label to obtain segmentation information, wherein the segmentation information is used for describing the disease information of the enterprise staff about the corresponding disease label; then the server rejects the segmented information with the preset interference corpus by using a preset rejection function to obtain residual information; the server extracts disease index data corresponding to the disease label from the residual information through a preset calling function; the server compares the disease index data with the standard range data, and when the disease index data is not in the standard range data, the disease index data is determined to be abnormal data; and finally, the server determines the disease label corresponding to the abnormal data as the abnormal disease label by using a preset corpus rule, and takes the employee information data corresponding to the abnormal disease label as the abnormal disease data.
The method comprises the steps that a server acquires employee information data of enterprise employees, wherein the enterprise employee information data comprises basic data of enterprise employees such as name, age, gender, position, post, performance, physical examination time and the like for describing the enterprise employees, when health data of the enterprise employees are analyzed, information about disease data in the employee information data needs to be screened out, the server searches required information data to be detected in the employee information data by using a Regular Expression, the Regular Expression (Regular Expression) is a logic formula for operating character strings, a 'rule character string' is formed by using a plurality of specific characters defined in advance and a combination of the specific characters, the 'rule character string' is used for expressing a filtering logic for the character string and is often used for retrieving and replacing texts conforming to a certain mode (rule), therefore, required information data to be detected is extracted from the employee information data of the enterprise employees.
After the server acquires the required information data to be detected, because the information data to be detected integrates a plurality of disease information data detected for enterprise employees, the server needs to segment the information data to be detected by using a preset segmentation function and a disease label, wherein a plurality of segmentation information are acquired after segmentation, and each segmentation information correspondingly describes analysis information data of a disease corresponding to a disease label, such as: the first section information describes the analysis information data of the enterprise staff member detected the diabetes disease label; the second segment of information describes the analysis information data that the business employee detected about the leukemia disease signature. The server also needs to screen the disease information data after acquiring the disease information data, and needs to remove the segment information with preset interference corpus, where the preset interference segment information refers to evaluation information when evaluating the cause of disease, such as: the evaluation information is: if no abnormity occurs, the server needs to analyze that abnormal disease information exists for the enterprise staff, so the server needs to remove the segmented information with the preset interference corpus to obtain the residual information.
The server can analyze employee information data in the remaining information after obtaining the remaining information, extract disease index data corresponding to the disease label from the remaining information, compare the disease index data with standard range data, and if the disease index data is not within the standard range data, indicate that the enterprise employee may have a disease corresponding to the disease label, such as: when blood routine detection is carried out, the content of white blood cells of a staff A of an enterprise is 9ml/L, the content of standard range data of the white blood cells is 3-6ml/L, the disease index data is abnormal, the server takes the abnormal data as abnormal data, then the server determines a disease label corresponding to the abnormal data as an abnormal disease label by using a preset corpus rule, and staff information data corresponding to the abnormal disease label is taken as abnormal disease data.
202. Generating a basic display table by adopting the attribute labels in the employee information data and the abnormal disease labels in the abnormal disease data, wherein the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data;
specifically, the server firstly obtains an attribute tag in the employee information data, wherein the attribute tag is used for indicating the property of the employee information data; then the server calculates the Cartesian product between the attribute tags and the abnormal disease tags to obtain a tag combination; and finally, the server establishes an initial display table based on the label combination, fills the employee information data and the abnormal disease data corresponding to the label combination into the initial display table by using a preset extraction function to obtain a basic display table, wherein the labels in the label combination are respectively a column label and a row label of the initial display table, and the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data.
The server acquires an attribute tag in the employee information, wherein the attribute tag refers to a tag describing the property of the employee information data, such as: name tags, age tags, gender tags, position tags, etc. of the employee information of the enterprise, and then the server calculates Cartesian products between attribute tags of the employee of the enterprise and the abnormal disease tags, where Cartesian products (Cartesian products) refer to Cartesian products of two sets X and Y, also called direct products, expressed as X × Y in mathematics, where the first object is one of the sets X and the second object is one of all possible ordered pairs in the set Y, whose expression is a × B { (X, Y) | X ∈ a ^ Y ∈ B }, that is, the server generates a set of all permutation combinations of the attribute tags and the abnormal disease tags, for example, the attribute tags in the employee information include: age, gender, abnormal disease signatures include: leukemia, diabetes, the server calculates the cartesian product (label combination) of the two as { (age, leukemia), (age, diabetes), (gender, leukemia), (gender, diabetes) }.
After the server obtains the label combination, the server establishes an initial display table by taking two labels in the label combination as a row label and a column label respectively, then fills data corresponding to the row label and the column label into the initial display table by using a preset extraction function, further generates a basic display table, and displays the relationship between the employee information data and the abnormal disease data.
203. Acquiring update information data of enterprise employees, integrating the employee information data and the update information data by using a preset integration function, generating an information data comparison graph of the enterprise employees, and storing the information data comparison graph into a target display set;
specifically, the server firstly acquires the update information data of the enterprise staff, and stores the update information data into a preset database; then the server acquires the entry time in the employee information data and the update time in the update information data, and the interval period between the entry time and the update time is obtained by calculating the entry time and the update time; and finally, the server integrates the employee information data and the updated information data by adopting a preset integration function, generates an information data comparison graph of the enterprise employees in the interval time period, and stores the information data comparison graph into a target display set.
Generally, an enterprise can arrange enterprise employees to perform physical examination within a period of time, for example, one enterprise employee physical examination is performed every year, enterprise employee information data collected by a server after a new enterprise employee physical examination is updated information data, and the server can integrate the updated information data of the enterprise employees and the employee information data to obtain a comparison trend of the two.
It should be noted that, the server obtains the update information data and stores the update information data in a preset database, where the preset database refers to a Redis database, and the Redis is an open-source log-type database written in ANSIC language, supporting network, and based on memory or capable of being persisted. In addition, response type programming is utilized to process the employee information data and the updated information data, and then an information data comparison graph of the enterprise employees is obtained.
204. Performing visual rendering on the basic display table to generate a target display set, wherein the target display set comprises a line graph, a bar graph, a scatter diagram, a K line graph and a box diagram which are generated on the basis of the basic display table;
specifically, the server inputs the basic display form into a preset data table to obtain a basic data table, and completes the entry of employee information data and abnormal disease data of enterprise employees; and the server converts the basic data table into a line graph, a bar graph, a scatter diagram, a K line graph and a box graph respectively by using a preset vector conversion function to generate a target display set.
When the server performs visual rendering on the basic display table, the basic display table carrying data is firstly input into a preset data table to obtain a basic data table, data needing to be displayed in multiple dimensions is determined, entry of employee information data and abnormal disease data of enterprise employees is completed, and then the server converts the data into charts in different display forms such as a line graph, a bar graph, a scatter diagram, a K line graph and a box diagram on the basis of the basic data table by using a preset vector conversion function. The preset vector conversion function is used as a vector graph library ZRender, and the line graph, the bar graph, the scatter graph, the K line graph and the box graph obtained through conversion are integrated together to generate a target display set.
205. And acquiring estimated risk data corresponding to the abnormal disease data of the enterprise staff and a corresponding risk solution in the target display set, combining the estimated risk data corresponding to the enterprise staff and the risk solution, and determining the health analysis result of the enterprise staff.
Specifically, the server firstly extracts abnormal disease data corresponding to the enterprise staff from the target display set to obtain target disease data; then the server calculates the basic similarity between the target disease data and the standard disease data in a preset rule solution library; when the basic similarity is larger than or equal to the standard threshold, the server acquires preset risk data corresponding to the standard disease data and a corresponding preset solution, and takes the preset risk data and the corresponding preset solution as estimated risk data and a risk solution of corresponding enterprise employees; and finally, the server combines the estimated risk data corresponding to the enterprise staff and the risk solution to determine the health analysis result of the enterprise staff.
Further, preset risk data corresponding to a plurality of disease labels and corresponding preset solutions are set in advance in a preset rule solution library, the server calculates the basic similarity between the target disease data and the standard disease data, the larger the value of the basic similarity is, the more similar the target disease data and the standard disease data is, the server takes the preset risk data corresponding to the standard disease data and the corresponding preset solutions as the estimated risk data and the risk solutions of corresponding enterprise employees, and the estimated risk data and the risk solutions are combined to obtain health analysis results of the enterprise employees. The health analysis result comprises clinical significance, concept explanation, formation reason, main symptoms, preventive measures, treatment methods, suggestions for reducing risk data, health management suggestions and the like of the corresponding diseases displayed according to the screened estimated risk data; the health management measures correspondingly displayed according to the screened estimated risk data can be as follows: plant placement, elastic work, regular physical examination and the like.
According to the embodiment of the invention, the abnormal disease data of the enterprise staff is obtained by segmenting and eliminating the staff information data of the enterprise staff, then the basic display table is generated by utilizing the attribute labels and the abnormal disease labels of the enterprise staff, the basic display table is visually rendered, the target display set of the abnormal disease data of the enterprise staff is displayed in a multi-dimensional mode, and finally the health analysis result of the enterprise staff is determined based on the target display set.
With reference to fig. 3, the method for analyzing health data of enterprise employees in the embodiment of the present invention is described above, and an embodiment of an apparatus for analyzing health data of enterprise employees in the embodiment of the present invention includes:
the acquiring module 301 is configured to acquire employee information data and a disease tag of an enterprise employee, segment and reject the employee information data by using a preset segmentation function, a preset rejection function and the disease tag in sequence to obtain remaining information, and determine abnormal disease data in the employee information data in the remaining information;
a generating module 302, configured to generate a basic display table by using the attribute tag in the employee information data and the abnormal disease tag in the abnormal disease data, where the basic display table is used to indicate a relationship between the employee information data and the abnormal disease data;
a display module 303, configured to perform visual rendering on the basic display table to generate a target display set, where the target display set includes a line graph, a bar graph, a scatter diagram, a K line graph, and a box graph generated based on the basic display table;
the determining module 304 is configured to obtain the estimated risk data corresponding to the abnormal disease data of the enterprise employee and the corresponding risk solution in the target display set, merge the estimated risk data corresponding to the enterprise employee and the risk solution, and determine a health analysis result of the enterprise employee.
According to the embodiment of the invention, the abnormal disease data of the enterprise staff is obtained by segmenting and eliminating the staff information data of the enterprise staff, then the basic display table is generated by utilizing the attribute labels and the abnormal disease labels of the enterprise staff, the basic display table is visually rendered, the target display set of the abnormal disease data of the enterprise staff is displayed in a multi-dimensional mode, and finally the health analysis result of the enterprise staff is determined based on the target display set.
Referring to fig. 4, another embodiment of the apparatus for analyzing health data of enterprise employees according to the embodiment of the present invention includes:
the acquiring module 301 is configured to acquire employee information data and a disease tag of an enterprise employee, segment and reject the employee information data by using a preset segmentation function, a preset rejection function and the disease tag in sequence to obtain remaining information, and determine abnormal disease data in the employee information data in the remaining information;
a generating module 302, configured to generate a basic display table by using the attribute tag in the employee information data and the abnormal disease tag in the abnormal disease data, where the basic display table is used to indicate a relationship between the employee information data and the abnormal disease data;
a display module 303, configured to perform visual rendering on the basic display table to generate a target display set, where the target display set includes a line graph, a bar graph, a scatter diagram, a K line graph, and a box graph generated based on the basic display table;
the determining module 304 is configured to obtain the estimated risk data corresponding to the abnormal disease data of the enterprise employee and the corresponding risk solution in the target display set, merge the estimated risk data corresponding to the enterprise employee and the risk solution, and determine a health analysis result of the enterprise employee.
Optionally, the obtaining module 301 may be further specifically configured to:
acquiring employee information data of enterprise employees, and searching required information data to be detected in the employee information data through a regular expression;
acquiring a disease label, and segmenting the information data to be detected by using a preset segmentation function and the disease label to obtain segmentation information, wherein the segmentation information is used for describing the disease information of the enterprise staff about the corresponding disease label;
rejecting the segmented information with preset interference corpora by using a preset rejection function to obtain residual information;
extracting disease index data corresponding to the disease label from the residual information through a preset calling function;
comparing the disease index data with standard range data, and determining the disease index data as abnormal data when the disease index data is not in the standard range data;
and determining a disease label corresponding to the abnormal data as an abnormal disease label by using a preset corpus rule, and taking employee information data corresponding to the abnormal disease label as abnormal disease data.
Optionally, the generating module 302 may be further specifically configured to:
acquiring an attribute tag in the employee information data, wherein the attribute tag is used for indicating the property of the employee information data;
calculating a Cartesian product between the attribute tag and the abnormal disease tag to obtain a tag combination;
establishing an initial display table based on the label combination, and filling employee information data and abnormal disease data corresponding to the label combination into the initial display table by using a preset extraction function to obtain a basic display table, wherein labels in the label combination are column labels and row labels of the initial display table respectively, and the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data.
Optionally, the display module 303 may be further specifically configured to:
inputting the basic display form into a preset data table to obtain a basic data table, and completing the input of employee information data and abnormal disease data of enterprise employees;
and respectively converting the basic data table into a line graph, a bar graph, a scatter diagram, a K line graph and a box graph by using a preset vector conversion function to generate a target display set.
Optionally, the determining module 304 may be further specifically configured to:
extracting abnormal disease data corresponding to the enterprise employees from the target display set to obtain target disease data;
calculating the basic similarity between the target disease data and the standard disease data in a preset rule solution library;
when the basic similarity is larger than or equal to a standard threshold, acquiring preset risk data corresponding to the standard disease data and a corresponding preset solution, and taking the preset risk data and the corresponding preset solution as estimated risk data and a risk solution corresponding to the enterprise staff;
and merging the estimated risk data corresponding to the enterprise staff and the risk solution, and determining the health analysis result of the enterprise staff.
Optionally, the apparatus for analyzing the health data of the enterprise employee further includes:
the integration module 305 is configured to obtain update information data of the enterprise employee, integrate the employee information data with the update information data by using a preset integration function, generate an information data comparison graph of the enterprise employee, and store the information data comparison graph in a target display set.
Optionally, the integration module 305 may be further specifically configured to:
acquiring update information data of the enterprise staff, and storing the update information data into a preset database;
acquiring an entry time in the employee information data and an update time in the update information data, and calculating the entry time and the update time to obtain an interval period between the entry time and the update time;
and integrating the employee information data and the updated information data by adopting a preset integration function, generating an information data comparison graph of the enterprise employees in the interval time period, and storing the information data comparison graph into a target display set.
According to the embodiment of the invention, the abnormal disease data of the enterprise staff is obtained by segmenting and eliminating the staff information data of the enterprise staff, then the basic display table is generated by utilizing the attribute labels and the abnormal disease labels of the enterprise staff, the basic display table is visually rendered, the target display set of the abnormal disease data of the enterprise staff is displayed in a multi-dimensional mode, and finally the health analysis result of the enterprise staff is determined based on the target display set.
Fig. 3 and 4 describe the apparatus for analyzing health data of employees of an enterprise in the embodiment of the present invention in detail from the perspective of a modular functional entity, and the apparatus for analyzing health data of employees of an enterprise in the embodiment of the present invention in detail from the perspective of hardware processing.
Fig. 5 is a schematic structural diagram of an analysis device for health data of an employee, according to an embodiment of the present invention, where the analysis device 500 for health data of an employee may generate a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 510 (e.g., one or more processors) and a memory 520, and one or more storage media 530 (e.g., one or more mass storage devices) storing applications 533 or data 532. Memory 520 and storage media 530 may be, among other things, transient or persistent storage. The program stored on storage medium 530 may include one or more modules (not shown), each of which may include a series of instructional operations in analysis device 500 on the health data of the employee of the enterprise. Still further, processor 510 may be configured to communicate with storage medium 530 to execute a series of instruction operations in storage medium 530 on analysis device 500 for health data of an employee of an enterprise.
The enterprise employee health data analysis device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input-output interfaces 560, and/or one or more operating systems 531, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art will appreciate that the configuration of the enterprise employee health data analysis device illustrated in FIG. 5 does not constitute a limitation of the enterprise employee health data analysis device, and may include more or fewer components than illustrated, or some components in combination, or a different arrangement of components.
The invention also provides an analysis device for health data of enterprise employees, which comprises a memory and a processor, wherein computer readable instructions are stored in the memory, and when being executed by the processor, the computer readable instructions cause the processor to execute the steps of the analysis method for the health data of the enterprise employees in the embodiments.
The invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, or a volatile computer readable storage medium, having stored therein instructions, which when run on a computer, cause the computer to perform the steps of the method for analyzing the health data of the employee of the enterprise.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for analyzing health data of enterprise employees is characterized by comprising the following steps:
acquiring employee information data and disease labels of enterprise employees, segmenting and rejecting the employee information data in sequence by using a preset segmentation function, a preset rejection function and the disease labels to obtain residual information, and determining abnormal disease data in the employee information data in the residual information;
generating a basic display table by adopting the attribute labels in the employee information data and the abnormal disease labels in the abnormal disease data, wherein the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data;
performing visual rendering on the basic display table to generate a target display set, wherein the target display set comprises a line graph, a bar graph, a scatter diagram, a K line graph and a box graph which are generated on the basis of the basic display table;
and acquiring estimated risk data corresponding to the abnormal disease data of the enterprise staff and a corresponding risk solution in the target display set, combining the estimated risk data corresponding to the enterprise staff and the risk solution, and determining the health analysis result of the enterprise staff.
2. The method for analyzing the health data of the employees of the enterprise according to claim 1, wherein the acquiring of the employee information data and the disease labels of the employees of the enterprise, the segmenting and removing of the employee information data are sequentially performed by using a preset segmentation function, a preset removal function and the disease labels to obtain the remaining information, and the determining of the abnormal disease data in the employee information data in the remaining information comprises:
acquiring employee information data of enterprise employees, and searching required information data to be detected in the employee information data through a regular expression;
acquiring a disease label, and segmenting the information data to be detected by using a preset segmentation function and the disease label to obtain segmentation information, wherein the segmentation information is used for describing the disease information of the enterprise staff about the corresponding disease label;
rejecting the segmented information with preset interference corpora by using a preset rejection function to obtain residual information;
extracting disease index data corresponding to the disease label from the residual information through a preset calling function;
comparing the disease index data with standard range data, and determining the disease index data as abnormal data when the disease index data is not in the standard range data;
and determining a disease label corresponding to the abnormal data as an abnormal disease label by using a preset corpus rule, and taking employee information data corresponding to the abnormal disease label as abnormal disease data.
3. The method for analyzing the health data of the employees of the enterprise as claimed in claim 1, wherein the generating a basic presentation table by using the attribute labels in the employee information data and the abnormal disease labels in the abnormal disease data, the basic presentation table indicating the relationship between the employee information data and the abnormal disease data comprises:
acquiring an attribute tag in the employee information data, wherein the attribute tag is used for indicating the property of the employee information data;
calculating a Cartesian product between the attribute tag and the abnormal disease tag to obtain a tag combination;
establishing an initial display table based on the label combination, and filling employee information data and abnormal disease data corresponding to the label combination into the initial display table by using a preset extraction function to obtain a basic display table, wherein labels in the label combination are column labels and row labels of the initial display table respectively, and the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data.
4. The method for analyzing health data of employees of an enterprise as claimed in claim 1, wherein said visually rendering said base presentation form to generate a target presentation set, said target presentation set comprising a line graph, a bar graph, a scatter graph, a K-line graph and a box graph generated based on said base presentation form comprises:
inputting the basic display form into a preset data table to obtain a basic data table, and completing the input of employee information data and abnormal disease data of enterprise employees;
and respectively converting the basic data table into a line graph, a bar graph, a scatter diagram, a K line graph and a box graph by using a preset vector conversion function to generate a target display set.
5. The method for analyzing health data of employees of an enterprise according to claim 1, wherein the obtaining of the pre-estimated risk data and the corresponding risk solution corresponding to the abnormal disease data of the employees of the enterprise in the target display set, combining the pre-estimated risk data and the risk solution corresponding to the employees of the enterprise, and determining the health analysis result of the employees of the enterprise comprises:
extracting abnormal disease data corresponding to the enterprise employees from the target display set to obtain target disease data;
calculating the basic similarity between the target disease data and the standard disease data in a preset rule solution library;
when the basic similarity is larger than or equal to a standard threshold, acquiring preset risk data corresponding to the standard disease data and a corresponding preset solution, and taking the preset risk data and the corresponding preset solution as estimated risk data and a risk solution corresponding to the enterprise staff;
and merging the estimated risk data corresponding to the enterprise staff and the risk solution, and determining the health analysis result of the enterprise staff.
6. The method for analyzing health data of enterprise employees according to any one of claims 1-5, wherein after generating a base presentation table by using attribute labels in the employee information data and abnormal disease labels in abnormal disease data, and the base presentation table is used for indicating a relationship between the employee information data and the abnormal disease data, the base presentation table is visually rendered to generate a target presentation set, and the target presentation set comprises a line graph, a bar graph, a scatter graph, a K-line graph and a box graph generated on the basis of the base presentation table, and further comprises:
acquiring the update information data of the enterprise staff, integrating the staff information data and the update information data by using a preset integration function, generating an information data comparison graph of the enterprise staff, and storing the information data comparison graph into a target display set.
7. The method for analyzing the health data of the employees of the enterprise according to claim 6, wherein the obtaining of the updated information data of the employees of the enterprise, integrating the employee information data with the updated information data by using a preset integration function, generating an information data comparison graph of the employees of the enterprise, and storing the information data comparison graph into a target display set comprises:
acquiring update information data of the enterprise staff, and storing the update information data into a preset database;
acquiring an entry time in the employee information data and an update time in the update information data, and calculating the entry time and the update time to obtain an interval period between the entry time and the update time;
and integrating the employee information data and the updated information data by adopting a preset integration function, generating an information data comparison graph of the enterprise employees in the interval time period, and storing the information data comparison graph into a target display set.
8. An apparatus for analyzing health data of an employee of an enterprise, the apparatus comprising:
the system comprises an acquisition module, a classification module and a processing module, wherein the acquisition module is used for acquiring employee information data and disease labels of enterprise employees, segmenting and removing the employee information data in sequence by using a preset segmentation function, a preset removal function and the disease labels to obtain residual information, and determining abnormal disease data in the employee information data in the residual information;
the generating module is used for generating a basic display table by adopting the attribute labels in the employee information data and the abnormal disease labels in the abnormal disease data, and the basic display table is used for indicating the relationship between the employee information data and the abnormal disease data;
the display module is used for performing visual rendering on the basic display table to generate a target display set, and the target display set comprises a line graph, a bar graph, a scatter diagram, a K line graph and a box graph which are generated on the basis of the basic display table;
and the determining module is used for acquiring the estimated risk data corresponding to the abnormal disease data of the enterprise staff and the corresponding risk solution in the target display set, combining the estimated risk data corresponding to the enterprise staff and the risk solution and determining the health analysis result of the enterprise staff.
9. An analysis device for health data of enterprise employees, comprising: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invokes the instructions in the memory to cause the analysis device of the health data of the employee to perform a method of analyzing the health data of the employee as recited in any one of claims 1-7.
10. A computer readable storage medium having instructions stored thereon, wherein the instructions, when executed by a processor, implement a method for analyzing health data of an employee of a business as recited in any one of claims 1-7.
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Application publication date: 20201204 |