CN116864062A - Health physical examination report data analysis management system based on Internet - Google Patents
Health physical examination report data analysis management system based on Internet Download PDFInfo
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Abstract
The invention belongs to the field of analysis and management of health examination report data, and particularly discloses an Internet-based analysis and management system for health examination report data, which comprises the following components: based on the disease proportion of each disease type in each characteristic group, the disease rule of each disease type in each characteristic group is analyzed. Through calculating the similarity of the target individual and each individual in the comprehensive crowd, individual corresponding disease types similar to the target individual are screened out, so that personalized health detection items can be recommended for the target individual, and the target individual can be ensured to carry out detection items which are most suitable for the physical condition of the user. Through obtaining the biggest prevalence of each disease category in each characteristic crowd, the disease category that the screening and target individual assorted characteristic crowd correspond, according to this to the healthy detection item of recommended to target individual, can improve health management efficiency, make health management more accurate and effective.
Description
Technical Field
The invention belongs to the field of analysis and management of health examination report data, and relates to an Internet-based analysis and management system for health examination report data.
Background
By analyzing a large amount of health examination report data, the health condition data among groups can be known, and according to the data, the system can provide personalized health management advice for each user, so that health detection items are recommended for the user in a targeted manner, the recommendation accuracy and the user satisfaction degree of the health detection items can be improved, and the user can find and prevent potential diseases early.
Traditional health detection projects often rely more on doctors' experience and subjective descriptions of users to recommend, and are subjective and uncertain. On the one hand, the existing recommendation method of the detection item depends on the overall information requirement of the user population more, and neglects consideration of individual variability, the current recommendation method may not accurately predict the requirement of the target individual, so that the recommendation result of the detection item is too general and specific detection item suggestions are not provided for the individual in a targeted manner, and thus, the user may need to spend more time and effort to screen and evaluate the effectiveness of the recommendation result, thereby increasing the health detection burden of the individual user.
On the other hand, the disease rules of various diseases are not fully considered to be summarized when the health detection project is recommended, and the pathogenesis and the disease rules of different diseases are different according to the disease differences among people with different age groups and sex characteristics of different diseases, so that the diseases can not be timely identified and recommended if the factors are not comprehensively considered when the detection project is recommended, and the recommendation result is lack of accuracy.
Disclosure of Invention
In view of this, in order to solve the problems set forth in the above background art, an internet-based health examination report data analysis and management system is now proposed.
The aim of the invention can be achieved by the following technical scheme: the invention provides a health examination report data analysis and management system based on the Internet, which comprises: the data acquisition module is used for acquiring the health indication data and the basic information corresponding to each physical examination report, marking the personnel to be examined as target individuals and acquiring the basic information of the target individuals.
And the individual disease type acquisition module is used for analyzing the disease types corresponding to the individuals based on the health indication data corresponding to the physical examination reports.
And the disease type analysis module is used for acquiring the corresponding basic information of each body and evaluating the disease rules of each disease type according to the basic information.
The first recommended detection item set acquisition module is used for screening out each prominent disease type from each disease type and recording the disease type as a first recommended detection item set.
And the sample individual screening module is used for comparing the basic information of each individual with the basic information of the target individual, calculating the similarity of the basic information of each individual and the basic information of the target individual, and further screening each sample individual.
The second recommended detection item set acquisition module is used for acquiring disease types corresponding to each specimen individual, acquiring each key disease type based on the disease rules of each disease type, and counting to obtain a second recommended detection item set.
And the final recommendation detection item determining module is used for summarizing the first recommendation detection item set and the second recommendation detection item set to obtain a final recommendation detection item set.
The information storage library is used for storing the normal value range of each health indication data corresponding to the individual physical examination report and the corresponding disease types when each health indication data is in abnormal conditions, and storing the corresponding detection items of each disease type.
In one embodiment, the basic information includes gender, age, height, and weight.
In one embodiment, the method for analyzing the disease type corresponding to each individual is as follows: and extracting a normal value range corresponding to each piece of health indication data from the information storage library, and extracting a disease type corresponding to each piece of health indication data when the health indication data is in an abnormal condition, and marking the disease type corresponding to each piece of health indication data.
Comparing each health indication data corresponding to each physical examination report with a normal value range of the corresponding health indication data, if the health indication data corresponding to a certain physical examination report is out of the normal value range, indicating that the health indication data corresponding to the physical examination report is in an abnormal condition, obtaining a disease type of the health indication data corresponding to the physical examination report, and marking the disease type as the disease type corresponding to the individual.
If the corresponding health indication data in a certain physical examination report are all in the normal value range of the corresponding health indication data, the disease type corresponding to the individual is marked as none, and then the disease type corresponding to the individual is obtained.
In one specific embodiment, the evaluating the disease law correspondence of each disease class includes: classifying and summarizing each body according to disease types to obtain each disease type corresponding to each body, dividing each body into each characteristic crowd according to basic information, and obtaining characteristic crowd of each individual corresponding to each disease type, wherein each characteristic crowd comprises sex characteristic crowd, age characteristic crowd, height characteristic crowd and weight characteristic crowd.
Counting the number of men and women of the individuals corresponding to each disease type, and recording as、/>，/>Number indicating disease type,/->Judging model according to disease law of sex characteristic crowdObtaining the disease rules of various disease types in the sex characteristic population.
Dividing age groups of age characteristic crowd according to set principle, obtaining age groups of individuals corresponding to each disease type according to ages of individuals corresponding to each disease type, and counting to obtain each disease typeNumber of individuals of disease variety at each age group，/>Number indicating age group>Calculating the prevalence of each disease category in each age group +.>Wherein->For the total number of individuals, the prevalence rates of all disease types in all age groups are compared with each other, and the age groups of all disease types are ordered according to the order of the prevalence rates from large to small, namely the prevalence rates of all disease types in age characteristic groups.
And analyzing the disease rules of each disease type in the height characteristic crowd and the weight characteristic crowd in a similar way according to the disease rule analysis mode of each disease type in the age characteristic crowd.
In a specific embodiment, the first recommendation detection item set obtaining manner is: based on the disease types corresponding to each individual, summarizing to obtain the number of the individuals corresponding to each disease type, and dividing the number of the individuals by the total number of the individuals to obtain the comprehensive disease occupation ratio of each disease type;
comparing the comprehensive disease occupation ratio of each disease type with a set disease occupation ratio limiting value, if the comprehensive disease occupation ratio of a certain disease type is larger than the set disease occupation ratio limiting value, marking the disease type as an outstanding disease type, counting to obtain each outstanding disease type, acquiring corresponding detection items of each outstanding disease type from an information storage library, and leading the detection items into a first recommended detection item set.
In a specific embodiment, the step of calculating the basic information similarity correspondence between each individual and the target individual includes: and comparing the sex in the basic information of each individual with the sex of the target individual, if the sex in the basic information of a certain individual is inconsistent with the sex of the target individual, marking the similarity of the basic information of the individual and the target individual as 0, otherwise, further correspondingly comparing the age, the height and the weight in the basic information of the individual with the age, the height and the weight of the target individual.
Calculating to obtain the basic information similarity of each individual and the target individualWherein->、/>、/>Respectively +.>Age, height, weight of the individual, and +.>Numbering individuals,/->，/>、/>、/>Age, height, weight of the target individual, < ->Is a natural constant.
In one embodiment, the screening step for screening each sample individual comprises: associating each individual with a target individualComparing the basic information similarity of the body with a preset similarity range, whenWhen indicate->The basic information similarity of the individual and the target individual is within the preset similarity range, and the individual is in the presence of the user's own personal information>、/>Respectively the minimum value and the maximum value of the preset similarity range, and then the +.>The individuals are marked as sample individuals, and each sample individual is obtained through statistics.
And obtaining detection items of disease types corresponding to each sample individual, and importing the detection items into a second recommended detection item set.
In a specific embodiment, the second recommendation test item set obtaining step is: s1, obtaining the deviation gender of each disease type based on a disease law judging model of the gender characteristic crowd, comparing the deviation gender of each disease type with the gender of the target individual, obtaining each disease type matched with the gender of the target individual, and marking the disease type as each primary disease type.
S2, marking the age stage of each disease type in the first position as an important age stage of each disease type, comparing the important age stage of each disease type with the age stage of a target individual to obtain each disease type matched with the age stage of the target individual, marking the disease type as each secondary disease type, and screening each secondary disease type from the height characteristic crowd and the weight characteristic crowd in the same way.
S3, after the operation of de-repeating items is carried out on each primary disease type and each secondary disease type, each primary disease type and each secondary disease type after the operation are matched, if a certain secondary disease type and a certain primary disease type are successfully matched, the secondary disease type is marked as an important disease type, each important disease type is obtained through statistics from each secondary disease, corresponding detection items of each important disease type are obtained, the detection items are further led into a second recommended detection item set, and de-duplication processing is carried out on the second recommended detection item set.
In a specific embodiment, the obtaining manner of the final recommended detection item set is as follows: comparing each detection item in the first recommended detection item set with each detection item in the second recommended detection item set, screening and removing repeated detection items to obtain each remaining detection item, wherein each obtained remaining detection item is the final recommended detection item set.
Compared with the prior art, the invention has the following beneficial effects: (1) According to the invention, the disease types corresponding to the individuals similar to the target individuals are screened out by calculating the similarity of the target individuals to each of the comprehensive crowds, so that personalized health detection items can be recommended for the target individuals, and the target individuals can be ensured to carry out detection items most suitable for the physical conditions of the individuals. Thus, not only can the time and effort of irrelevant or repeated detection of the target individual be reduced, but also the efficiency and accuracy of health management can be improved.
(2) According to the invention, the maximum prevalence rate of each disease type in each characteristic crowd is obtained, and the disease type corresponding to the characteristic crowd matched with the target individual is screened, so that the health detection item is recommended to the target individual, the health management efficiency can be improved, and the health management is more accurate and effective. Meanwhile, the method can help the target individual to preliminarily know the health hidden trouble existing in the basic information of the target individual, strengthen the attention and the knowledge of the target individual on the health, and guide the target individual to develop good living habits and health behaviors, so that the overall health level is improved.
(3) The invention analyzes the disease rules of each disease type in each characteristic group based on the disease occupation ratio of each disease type in each characteristic group, and can provide important reference for disease prevention. For example, if a characteristic population is found to have a high prevalence in a disease, preventive measures can be targeted to reduce the risk of the disease. Therefore, the detection items can be recommended for target individuals in a targeted mode, and medical institutions can be helped to know the illness rules in the characteristic crowd.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the system module connection of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides an analysis and management system for health examination report data based on internet, the system comprises: the system comprises a data acquisition module, an individual disease type acquisition module, a disease type analysis module, a first recommended detection item set acquisition module, a sample individual screening module, a second recommended detection item set acquisition module, a final recommended detection item determination module and an information storage library. The data acquisition module is connected with the individual disease type acquisition module, the individual disease type acquisition module is connected with the disease type analysis module respectively, the first recommendation detection item set acquisition module is connected with the disease type analysis module, the sample individual screening module is connected with the second recommendation detection item set acquisition module, the final recommendation detection item determination module is connected with the first recommendation detection item set acquisition module and the second recommendation detection item set acquisition module respectively, and the information storage library is connected with the individual disease type acquisition module, the first recommendation detection item set acquisition module and the second recommendation detection item set acquisition module respectively.
The data acquisition module is used for acquiring the health indication data and the basic information corresponding to each physical examination report, marking the personnel to be examined as target individuals and acquiring the basic information of the target individuals.
The individual disease type acquisition module is used for analyzing the disease types corresponding to the individuals based on the health indication data corresponding to the physical examination reports.
In a specific embodiment of the present invention, the basic information includes gender, age, height and weight.
In a specific embodiment of the present invention, the method for analyzing the disease types corresponding to the individual bodies includes: and extracting a normal value range corresponding to each piece of health indication data from the information storage library, and extracting a disease type corresponding to each piece of health indication data when the health indication data is in an abnormal condition, and marking the disease type corresponding to each piece of health indication data.
Comparing each health indication data corresponding to each physical examination report with a normal value range of the corresponding health indication data, if the health indication data corresponding to a certain physical examination report is out of the normal value range, indicating that the health indication data corresponding to the physical examination report is in an abnormal condition, obtaining a disease type of the health indication data corresponding to the physical examination report, and marking the disease type as the disease type corresponding to the individual.
If the corresponding health indication data in a certain physical examination report are all in the normal value range of the corresponding health indication data, the disease type corresponding to the individual is marked as none, and then the disease type corresponding to the individual is obtained.
Exemplary, blood biochemical index related data including blood pressure, blood lipid, and blood glucose are extracted from the health index data corresponding to each physical examination report, and the health index corresponding to cardiovascular organ is evaluatedWherein->、/>、/>Respectively represent the blood pressure, blood fat and blood sugar of the ith individual>、/>、/>Maximum normal value corresponding to blood biochemical index related data respectively>、/>、/>Respectively corresponding to the minimum normal value and the +_f of the blood biochemical index related data>、/>、/>The health index effects corresponding to blood pressure, blood fat and blood sugar respectively account for the weight.
Specifically, the above-mentioned analysis of the disease type of the cardiovascular organ is performed by taking the blood biochemical index-related data as an example, but the health index data in the specific health examination report is not limited thereto, and may include immune function index-related data, tumor marker-related data, imaging examination result-related data, and the like.
The disease type analysis module is used for acquiring corresponding basic information of each individual, and accordingly evaluating the disease rules of each disease type.
In a specific embodiment of the present invention, the evaluating the disease law of each disease class includes: classifying and summarizing each body according to disease types to obtain each disease type corresponding to each body, dividing each body into each characteristic crowd according to basic information, and obtaining characteristic crowd of each individual corresponding to each disease type, wherein each characteristic crowd comprises sex characteristic crowd, age characteristic crowd, height characteristic crowd and weight characteristic crowd.
Counting the number of men and women of the individuals corresponding to each disease type, and recording as、/>，/>Number indicating disease type,/->Judging model according to disease law of sex characteristic crowdObtaining the disease rules of various disease types in the sex characteristic population.
Dividing age groups of age characteristic crowd according to a set principle, obtaining age groups of individuals corresponding to each disease type according to ages of individuals corresponding to each disease type, and counting to obtain individual numbers of each disease type in each age group，/>Number indicating age group>Calculating the prevalence of each disease category in each age group +.>Wherein->For the total number of individuals, the prevalence rates of all disease types in all age groups are compared with each other, and the age groups of all disease types are ordered according to the order of the prevalence rates from large to small, namely the prevalence rates of all disease types in age characteristic groups.
The total number of individuals is obtained by statistics of individual physical examination reports.
And analyzing the disease rules of each disease type in the height characteristic crowd and the weight characteristic crowd in a similar way according to the disease rule analysis mode of each disease type in the age characteristic crowd.
In addition to the above features, each feature group includes a genetic background feature group, a lifestyle feature group, a professional feature group, and the like, and the exemplary steps of analyzing the disease law for the professional feature group are as follows: summarizing the occupational fields of the diseases corresponding to the individuals to obtain the number of the individuals of the diseases in the occupational fields, and recording as，/>Number representing professional field->Calculating the prevalence rate of each disease category in each occupational areaComparing the prevalence of each disease type in each occupational area, and ordering the occupational areas of each disease type according to the order of the prevalence from big to small, namelyThe disease rules of various disease types in the characteristic population of the professional field.
The evaluation of disease rules of various diseases can help doctors and researchers to discover diseases earlier and perform early intervention, and by searching potential risk factors and related characteristics in each characteristic population, the accuracy of early diagnosis can be improved, and appropriate treatment measures can be timely taken. In addition, by knowing the law of illness, medical resources can be better distributed, reasonable utilization of the resources is ensured, for example, if the prevalence rate in a certain characteristic crowd is higher, corresponding medical equipment, medicines and human resources can be arranged in advance to meet the demands thereof.
The invention analyzes the disease rules of each disease type in each characteristic group based on the disease occupation ratio of each disease type in each characteristic group, and can provide important reference for disease prevention. For example, if a characteristic population is found to have a high prevalence in a disease, preventive measures can be targeted to reduce the risk of the disease.
The first recommended detection item set acquisition module is used for screening out each prominent disease type from each disease type and recording the disease type as a first recommended detection item set.
In a specific embodiment of the present invention, the first recommendation detection item set obtaining manner is: based on the disease types corresponding to each individual, summarizing to obtain the number of the individuals corresponding to each disease type, and dividing the number of the individuals by the total number of the individuals to obtain the comprehensive disease occupation ratio of each disease type;
comparing the comprehensive disease occupation ratio of each disease type with a set disease occupation ratio limiting value, if the comprehensive disease occupation ratio of a certain disease type is larger than the set disease occupation ratio limiting value, marking the disease type as an outstanding disease type, counting to obtain each outstanding disease type, acquiring corresponding detection items of each outstanding disease type from an information storage library, and leading the detection items into a first recommended detection item set.
The set limit value of the disease occupation ratio is as follows，/>。
The sample individual screening module is used for comparing the basic information of each individual with the basic information of the target individual, calculating the similarity of the basic information of each individual and the basic information of the target individual, and further screening each sample individual.
In a specific embodiment of the present invention, the step of calculating the basic information similarity correspondence between each individual and the target individual includes: and comparing the sex in the basic information of each individual with the sex of the target individual, if the sex in the basic information of a certain individual is inconsistent with the sex of the target individual, marking the similarity of the basic information of the individual and the target individual as 0, otherwise, further correspondingly comparing the age, the height and the weight in the basic information of the individual with the age, the height and the weight of the target individual.
Calculating to obtain the basic information similarity of each individual and the target individualWherein->、/>、/>Respectively +.>Age, height, weight of the individual, and +.>Numbering individuals,/->，/>、/>、/>Age, height, weight of the target individual, < ->Is a natural constant.
In a specific embodiment of the present invention, the screening step for screening each sample individual includes: comparing the basic information similarity of each individual and the target individual with a preset similarity range, and whenWhen indicate->The basic information similarity of the individual and the target individual is within the preset similarity range, and the individual is in the presence of the user's own personal information>、/>Respectively the minimum value and the maximum value of the preset similarity range, and then the +.>The individuals are marked as sample individuals, and each sample individual is obtained through statistics.
And obtaining detection items of disease types corresponding to each sample individual, and importing the detection items into a second recommended detection item set.
According to the invention, the disease types corresponding to the individuals similar to the target individuals are screened out by calculating the similarity of the target individuals to each of the comprehensive crowds, so that personalized health detection items can be recommended for the target individuals, and the target individuals can be ensured to carry out detection items most suitable for the physical conditions of the individuals. Thus, not only can the time and effort of irrelevant or repeated detection of the target individual be reduced, but also the efficiency and accuracy of health management can be improved.
The second recommended detection item set acquisition module is used for acquiring disease types corresponding to each specimen individual, acquiring each key disease type based on the disease rules of each disease type, and counting to obtain a second recommended detection item set.
In a specific embodiment of the present invention, the second recommendation detection item set obtaining step is: s1, obtaining the deviation gender of each disease type based on a disease law judging model of the gender characteristic crowd, comparing the deviation gender of each disease type with the gender of the target individual, obtaining each disease type matched with the gender of the target individual, and marking the disease type as each primary disease type.
Specifically, the preferential sex of each disease type refers to the sex corresponding to the maximum ratio of the number of men and women. When the number of the male and female types is the same, the biased sex of the disease type is recorded as matching the sex of the target individual, i.e. the disease type is the primary disease type.
S2, marking the age stage of each disease type in the first position as an important age stage of each disease type, comparing the important age stage of each disease type with the age stage of a target individual to obtain each disease type matched with the age stage of the target individual, marking the disease type as each secondary disease type, and screening each secondary disease type from the height characteristic crowd and the weight characteristic crowd in the same way.
S3, after the operation of de-repeating items is carried out on each primary disease type and each secondary disease type, each primary disease type and each secondary disease type after the operation are matched, if a certain secondary disease type and a certain primary disease type are successfully matched, the secondary disease type is marked as an important disease type, each important disease type is obtained through statistics from each secondary disease, corresponding detection items of each important disease type are obtained, the detection items are further led into a second recommended detection item set, and de-duplication processing is carried out on the second recommended detection item set.
According to the invention, the maximum prevalence rate of each disease type in each characteristic crowd is obtained, and the disease type corresponding to the characteristic crowd matched with the target individual is screened, so that the health detection item is recommended to the target individual, the health management efficiency can be improved, and the health management is more accurate and effective. Meanwhile, the method can help the target individual to preliminarily know the health hidden trouble existing in the basic information of the target individual, strengthen the attention and the knowledge of the target individual on the health, and guide the target individual to develop good living habits and health behaviors, so that the overall health level is improved.
The final recommendation detection item determining module is used for summarizing the first recommendation detection item set and the second recommendation detection item set to obtain a final recommendation detection item set.
In a specific embodiment of the present invention, the obtaining manner of the final recommended detection item set is: comparing each detection item in the first recommended detection item set with each detection item in the second recommended detection item set, screening and removing repeated detection items to obtain each remaining detection item, wherein each obtained remaining detection item is the final recommended detection item set.
The test items include blood routine test items, liver function test items, electrocardiographic examination test items, and the like.
Each detection item in the first recommended detection item set refers to disease types screened out in the comprehensive crowd according to the judgment standard that the prevalence exceeds a set limit value of the prevalence ratio, namely, diseases which are relatively common in most people. This collection will typically include some common chronic disease, infectious disease, and other health risk factor related test items. By detecting these items, potential health problems can be discovered early and preventive or therapeutic measures can be taken in time to improve the overall health level of the population.
Each detection item in the second recommended detection item set refers to disease types screened out in a specific crowd according to the criterion of higher prevalence. The second set of recommended detection items is more focused than the first set of recommended detection items on more common or highly-developed diseases in a particular group of people. For example, in specific crowds such as different age groups and sexes, certain specific diseases have high risk, and by carrying out detection items of the specific crowds, the health state of a target individual can be known more accurately, and related diseases can be found and prevented in early stage.
The information storage library is used for storing a normal value range of each health indication data corresponding to the individual physical examination report and disease types corresponding to the abnormal condition of each health indication data, and storing detection items corresponding to each disease type.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.
Claims (9)
1. An internet-based health examination report data analysis and management system, which is characterized in that the system comprises:
the data acquisition module is used for acquiring the health indication data and the basic information corresponding to each physical examination report, marking the personnel to be examined as target individuals and acquiring the basic information of the target individuals;
the individual disease type acquisition module is used for analyzing the disease types corresponding to the individuals based on the health indication data corresponding to the physical examination reports;
the disease type analyzing module is used for acquiring corresponding basic information of each body and evaluating the disease rules of each disease type according to the basic information;
the first recommended detection item set acquisition module is used for screening out each prominent disease type from each disease type and marking the disease type as a first recommended detection item set;
the sample individual screening module is used for comparing the basic information of each individual with the basic information of the target individual, calculating the similarity of the basic information of each individual and the basic information of the target individual, and further screening each sample individual;
the second recommended detection item set acquisition module is used for acquiring disease types corresponding to each specimen individual, acquiring each key disease type based on the disease rules of each disease type, and counting to obtain a second recommended detection item set;
the final recommendation detection item determining module is used for summarizing the first recommendation detection item set and the second recommendation detection item set to obtain a final recommendation detection item set;
the information storage library is used for storing the normal value range of each health indication data corresponding to the individual physical examination report and the corresponding disease types when each health indication data is in abnormal conditions, and storing the corresponding detection items of each disease type.
2. The internet-based health examination report data analysis and management system according to claim 1, wherein: the basic information includes sex, age, height and weight.
3. The internet-based health examination report data analysis and management system according to claim 1, wherein: the analysis method for analyzing the disease types corresponding to the individuals comprises the following steps:
extracting normal value ranges corresponding to the health indication data from the information storage library, extracting disease types corresponding to the abnormal condition of the health indication data, and marking the disease types as the disease types corresponding to the health indication data;
comparing each health indication data corresponding to each physical examination report with a normal value range of the corresponding health indication data, if the health indication data corresponding to a certain physical examination report is out of the normal value range, indicating that the health indication data corresponding to the individual physical examination report is in an abnormal condition, obtaining a disease type of the health indication data corresponding to the individual physical examination report, and marking the disease type as the disease type corresponding to the individual;
if the corresponding health indication data in a certain physical examination report are all in the normal value range of the corresponding health indication data, the disease type corresponding to the individual is marked as none, and then the disease type corresponding to the individual is obtained.
4. The internet-based health examination report data analysis and management system according to claim 2, wherein: the corresponding content for evaluating the disease rules of various diseases comprises the following steps:
classifying and summarizing each body according to disease types to obtain each disease type corresponding to each individual, dividing each body into each characteristic group according to basic information, and obtaining characteristic groups of each individual corresponding to each disease type, wherein each characteristic group comprises sex characteristic groups, age characteristic groups, height characteristic groups and weight characteristic groups;
counting the number of men and women of the individuals corresponding to each disease type, and recording as，/>Number indicating disease type,/->Judging model according to disease law of sex characteristic crowdObtaining the disease rules of various disease types in the sex characteristic population;
dividing age groups of age characteristic crowd according to a set principle, obtaining age groups of individuals corresponding to each disease type according to ages of individuals corresponding to each disease type, and counting to obtain individual numbers of each disease type in each age group，Number indicating age group>Calculate the patients of each disease category at each ageDisease rate->Wherein->Comparing the prevalence of each disease type in each age stage for the total number of individuals, and sequencing the age stages of each disease type according to the sequence from the high prevalence to the low prevalence, namely, sequencing the prevalence of each disease type in age characteristic population;
and analyzing the disease rules of each disease type in the height characteristic crowd and the weight characteristic crowd in a similar way according to the disease rule analysis mode of each disease type in the age characteristic crowd.
5. The internet-based health examination report data analysis and management system of claim 4, wherein: the first recommended detection item set obtaining mode is as follows:
based on the disease types corresponding to each individual, summarizing to obtain the number of the individuals corresponding to each disease type, and dividing the number of the individuals by the total number of the individuals to obtain the comprehensive disease occupation ratio of each disease type;
comparing the comprehensive disease occupation ratio of each disease type with a set disease occupation ratio limiting value, if the comprehensive disease occupation ratio of a certain disease type is larger than the set disease occupation ratio limiting value, marking the disease type as an outstanding disease type, counting to obtain each outstanding disease type, acquiring corresponding detection items of each outstanding disease type from an information storage library, and leading the detection items into a first recommended detection item set.
6. The internet-based health examination report data analysis and management system according to claim 1, wherein: the step of calculating the basic information similarity correspondence between each individual and the target individual comprises the following steps:
comparing the sex in the basic information of each individual with the sex of the target individual, if the sex in the basic information of a certain individual is inconsistent with the sex of the target individual, marking the similarity of the basic information of the individual and the target individual as 0, otherwise, further correspondingly comparing the age, the height and the weight in the basic information of the individual with the age, the height and the weight of the target individual;
calculating to obtain the basic information similarity of each individual and the target individualWherein->Respectively +.>Age, height, weight of the individual, and +.>Numbering individuals,/->，/>Age, height, weight of the target individual, < ->Is a natural constant.
7. The internet-based health examination report data analysis and management system of claim 6, wherein: the screening step of screening each sample individual comprises the following steps:
comparing the basic information similarity of each individual and the target individual with a preset similarity range, and whenWhen indicate->The basic information similarity of the individual and the target individual is within the preset similarity range, and the individual is in the presence of the user's own personal information>Respectively the minimum value and the maximum value of the preset similarity range, and then the +.>The individual is marked as a sample individual, and each sample individual is obtained through statistics;
and obtaining detection items of disease types corresponding to each sample individual, and importing the detection items into a second recommended detection item set.
8. The internet-based health examination report data analysis and management system of claim 4, wherein: the second recommended detection item set obtaining step comprises the following steps:
s1, obtaining the deviation gender of each disease type based on a disease law judging model of a gender characteristic crowd, comparing the deviation gender of each disease type with the gender of a target individual to obtain each disease type matched with the gender of the target individual, and marking the disease type as each primary disease type;
s2, marking the age stage of each disease type in the first position as an important age stage of each disease type, comparing the important age stage of each disease type with the age stage of a target individual to obtain each disease type matched with the age stage of the target individual, marking the disease type as each secondary disease type, and screening each secondary disease type from the height characteristic crowd and the weight characteristic crowd in the same way;
s3, after the operation of de-repeating items is carried out on each primary disease type and each secondary disease type, each primary disease type and each secondary disease type after the operation are matched, if a certain secondary disease type and a certain primary disease type are successfully matched, the secondary disease type is marked as an important disease type, each important disease type is obtained through statistics from each secondary disease, corresponding detection items of each important disease type are obtained, the detection items are further led into a second recommended detection item set, and de-duplication processing is carried out on the second recommended detection item set.
9. The internet-based health examination report data analysis and management system according to claim 1, wherein: the final recommended detection item set is obtained in the following manner: comparing each detection item in the first recommended detection item set with each detection item in the second recommended detection item set, screening and removing repeated detection items to obtain each remaining detection item, wherein each obtained remaining detection item is the final recommended detection item set.
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