CN120767003B - Artificial Intelligence-Based Early Warning and Prevention System for Childhood Infectious Diseases - Google Patents
Artificial Intelligence-Based Early Warning and Prevention System for Childhood Infectious DiseasesInfo
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Abstract
本发明涉及感染性疾病监测技术领域，具体涉及基于人工智能的儿童感染性疾病早期预警及防控系统。该系统获取当前时间段内患病儿童的致病微生物类型和化验数据；根据致病微生物类型在当前时间段内对应的患病儿童以及与历史时间段内对应的患病儿童，筛选出目标微生物类型；将目标微生物类型对应的患病儿童作为目标儿童，将目标儿童偏高的化验数据作为目标数据，根据目标儿童的变化情况和目标数据的出现情况，获取当前时刻下儿童感染性疾病的流行程度判断是否进行儿童感染性疾病的早期预警及防控。本发明通过实时准确获取儿童感染性疾病的流行程度，使得更准确及时进行早期预警及防控，有效降低了儿童感染性疾病诊断延误和防控反应滞后的情况。
This invention relates to the field of infectious disease surveillance technology, specifically to an artificial intelligence-based early warning and control system for childhood infectious diseases. The system acquires the pathogenic microorganism types and laboratory data of sick children within the current time period; it filters target microorganism types based on the sick children corresponding to the pathogenic microorganism types in the current time period and their corresponding sick children in historical time periods; it designates sick children corresponding to the target microorganism types as target children, and identifies target data based on elevated laboratory data of the target children; and it obtains the prevalence of childhood infectious diseases at the current moment based on changes in the target children and the occurrence of target data to determine whether early warning and control measures for childhood infectious diseases should be implemented. This invention, by accurately acquiring the prevalence of childhood infectious diseases in real time, enables more accurate and timely early warning and control, effectively reducing delays in diagnosis and lag in response to infectious diseases in children.
Description
Technical Field
The invention relates to the technical field of infectious disease monitoring, in particular to an early warning, prevention and control system for children infectious diseases based on artificial intelligence.
Background
The childhood infectious diseases are common infectious diseases caused by bacteria, viruses, fungi or parasites and other pathogens, and have the characteristics of high transmission speed and complex pathogenic mechanism. Since the immune system of children is not yet developed and mature, the infection risk is significantly higher than that of adults, and the disease progress rapidly, and partial diseases (such as severe influenza, hand-foot-mouth disease, streptococcus pneumoniae infection and the like) can cause serious complications and even endanger lives. Therefore, early warning and prevention and control are of great significance in pediatric clinics and public health management.
In the existing method, doctors early warn and prevent and control the children infectious diseases through clinical symptoms of sick children, but in actual conditions, the pathogens of the children infectious diseases are various, the disease transmission paths are complex, and different sick children can cause different clinical symptoms due to the difference of the children, so that the complexity of early warn is increased, meanwhile, the problems of delayed diagnosis and delayed prevention and control response of the children infectious diseases are easily caused by artificial subjective judgment, and the control of the children infectious diseases is not facilitated.
Disclosure of Invention
In order to solve the technical problems of delayed diagnosis and delayed prevention and control reaction of the childhood infectious diseases, the invention aims to provide an early childhood infectious disease early warning and prevention and control system based on artificial intelligence, and the adopted technical scheme is as follows:
the embodiment of the invention provides an artificial intelligence-based early warning, prevention and control system for infectious diseases of children, which comprises the following components:
the data acquisition module is used for acquiring an electronic medical record of each sick child in the current time period, wherein the electronic medical record comprises pathogenic microorganism types and various assay data;
the target microorganism type acquisition module is used for screening out target microorganism types with prominent pathogenicity according to the number of sick children corresponding to each pathogenic microorganism type in the current time period and the difference of the number of sick children corresponding to the historical time period;
The popularity acquisition module is used for taking all sick children corresponding to the target microorganism type in the current time period as target children, taking assay data of the target children which are higher as target data, and acquiring the popularity of the children infectious diseases at the current moment according to the change condition of the target children in the current time period and the occurrence condition of each target data in the target children;
And the data processing module is used for judging whether early warning and prevention and control of the children infectious diseases are performed at the current moment based on the popularity.
Further, the method for obtaining the target microorganism type comprises the following steps:
Obtaining the prominence degree of each pathogenic microorganism type according to the corresponding diseased child ratio of each pathogenic microorganism type in the current time period and the difference of the corresponding diseased child ratio in the historical time period;
The type of pathogenic microorganism corresponding to the greatest degree of prominence is taken as the target type of microorganism.
Further, the method for obtaining the protruding degree comprises the following steps:
For any pathogenic microorganism type, obtaining the ratio of the number of the sick children corresponding to the pathogenic microorganism type in the current time period to the number of all the sick children in the current time period as a first reference value;
acquiring the ratio of the number of the sick children corresponding to the pathogenic microorganism type in the historical time period to the number of all the sick children in the historical time period as a second reference value;
normalizing the difference value between the first reference value and the second reference value to obtain an adjustment weight;
the product of the weight and the first reference value will be adjusted as the degree of prominence of the type of pathogenic microorganism.
Further, the early warning and prevention and control system for the infectious diseases of children based on artificial intelligence further comprises:
when at least two pathogenic microorganism types corresponding to the maximum protruding degree exist, obtaining the number of diseased children corresponding to each pathogenic microorganism type corresponding to the maximum protruding degree in the current time period as a first number;
The largest first number of corresponding pathogenic microorganism types is taken as the target microorganism type.
Further, the popularity obtaining method comprises the following steps:
According to the change condition of the target child in the current time period, obtaining the epidemic tendency degree of the child infectious disease at the current moment;
Obtaining the disease assay similarity of the target microorganism type at the current moment according to the occurrence ratio of each target data in the target children;
and (3) normalizing the product of the epidemic tendency degree and the disease assay similarity degree to obtain the epidemic degree of the childhood infectious disease at the current moment.
Further, the method for obtaining the popularity tendency degree comprises the following steps:
Uniformly dividing the current time period into local time periods, and acquiring the number of target children in each local time period as a reference number;
acquiring a potential disease stage and a epidemic disease stage in the current time period according to the change condition of the reference quantity;
taking the maximum reference number in the potential disease stage as the potential representative number, and taking the local time periods in the disease epidemic stage as the analysis time periods;
for any analysis period, taking the ratio of the reference number to the potential representative number of the analysis period as a disease prevalence analysis value of the analysis period;
Taking the difference value of the reference number of the analysis time period and the previous adjacent local time period as a first value of the analysis time period;
Taking the ratio of the first value to the reference number of the adjacent local time period before the analysis time period as the reference weight of the analysis time period;
taking the product of the disease prevalence analysis value and the reference weight as a local disease prevalence reference value for the analysis period;
The average value of the local disease prevalence reference values of all analysis periods is normalized as the prevalence trend of the childhood infectious disease at the current time.
Further, the method for acquiring the disease potential stage and the disease epidemic stage in the current time period comprises the following steps:
Acquiring a first value of each local time period, taking the local time period corresponding to the maximum first value as a segmentation time period, and taking the time periods corresponding to the segmentation time period and all the previous local time periods as potential stages of the disease;
The time period corresponding to all the local time periods after the divided time period is taken as the disease epidemic stage.
Further, the early warning and prevention and control system for the infectious diseases of children based on artificial intelligence further comprises:
when the maximum first value corresponds to a plurality of local time periods, the local time period corresponding to the maximum first value which appears for the first time is taken as the segmentation time period.
Further, the method for obtaining the similarity of the disease assay comprises the following steps:
For any target data, taking the ratio of the number of target children containing the target data to the number of all target children as the duty ratio degree of the target data;
and taking the addition result of the duty ratio degree of all the target data as the disease test similarity degree of the target microorganism type at the current moment.
Further, the method for judging whether early warning and prevention and control of the children infectious diseases are performed at the current moment based on the popularity degree comprises the following steps:
When the popularity is greater than a preset popularity threshold, early warning and prevention and control of the children infectious diseases are required at the current moment;
When the popularity is smaller than or equal to a preset popularity threshold value, early warning and prevention and control of the children infectious diseases are not needed at the current moment.
The invention has the following beneficial effects:
According to the method, firstly, the number of the sick children corresponding to each pathogenic microorganism type in the current time period and the difference of the number of the sick children corresponding to the historical time period are used for screening out the target microorganism types with prominent pathogenicity, the pathogenic microorganism types possibly causing the epidemic of the infectious diseases of the children in the current time period are accurately determined, the follow-up accurate and efficient analysis of the epidemic situation of the infectious diseases of the children at the current time is facilitated, the sick children corresponding to the target microorganism types in the current time period are further taken as target children, the assay data of the target children which are higher are taken as target data, the epidemic degree of the infectious diseases of the children at the current time is obtained according to the change situation of the target children in the current time period and the occurrence situation of each target data in the target children, the severity of the epidemic of the infectious diseases of the children at the current time is accurately reflected, and then the early warning and prevention and control of the infectious diseases of the children at the current time are accurately judged based on the epidemic degree, the early warning and prevention of the infectious diseases of the children are enabled to be more accurately and timely carried out, the early warning and prevention and delay of the infectious diseases of the children and the prevention and response lag of the children are effectively reduced, and the control of the infectious diseases of the children is facilitated to be further controlled.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an early warning and prevention and control method for childhood infectious diseases based on artificial intelligence according to an embodiment of the invention;
FIG. 2 is a flowchart of a method for obtaining a target microorganism type according to an embodiment of the present invention;
FIG. 3 is a flowchart of a method for obtaining popularity in accordance with one embodiment of the present invention;
FIG. 4 is a block diagram of an early warning and prevention and control system for childhood infectious diseases based on artificial intelligence according to an embodiment of the present invention;
Fig. 5 is a schematic diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description is given below of the early warning and prevention and control method for the childhood infectious diseases based on artificial intelligence according to the invention, which is provided by combining the accompanying drawings and the preferred embodiment. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides a specific scheme of an early warning and prevention and control method for children infectious diseases based on artificial intelligence, which is specifically described below with reference to the accompanying drawings.
Example 1:
the invention provides an early warning and prevention and control method for children infectious diseases based on artificial intelligence, referring to fig. 1, which shows a schematic flow chart of the early warning and prevention and control method for children infectious diseases based on artificial intelligence, which comprises the following steps:
And S1, acquiring an electronic medical record of each sick child in the current time period, wherein the electronic medical record comprises pathogenic microorganism types and various assay data.
It is known that childhood infectious diseases (such as influenza, pneumonia, hand-foot-and-mouth disease, etc.) are usually manifested by symptoms such as fever, vomiting, diarrhea, cough, shortness of breath, etc., which can cause the childhood to feel uncomfortable and affect normal life and rest, and severe infections can also cause complications, even endangering the childhood life when serious. Because infectious diseases can cause damage to the immune system of children, especially for infants and children with incomplete mature immune system and children with weak immunity, the children can be in a state of weakness and easy infection for a long time after infection, so that early warning and prevention and control of the infectious diseases of children are more needed.
In order to analyze the epidemic situation of the childhood infectious diseases in real time and control the childhood infectious diseases in time, the embodiment obtains the electronic medical record of each sick child in the current pediatric time period through a hospital database, wherein the electronic medical record contains pathogenic microorganism types and various assay data. In this embodiment, the duration of the current time period is set to 30 days, and the practitioner can set the size of the current time period according to the actual situation, which is not limited herein. The ending time of the current time period is necessarily the current time. The disease-causing microorganism type includes virus, bacteria, fungi, etc., and the assay data includes serum alanine aminotransferase, aspartic acid aminotransferase, leucocyte, etc., wherein the types of assay data are identical for each sick child.
And S2, screening out target microorganism types with prominent pathogenicity according to the number of sick children corresponding to each pathogenic microorganism type in the current time period and the difference of the number of sick children corresponding to the historical time period.
In particular, the epidemic childhood infectious disease is usually caused by a certain pathogenic microorganism type, and thus, the present embodiment analyzes according to the number of sick children corresponding to each pathogenic microorganism type in the current period, and when the number of sick children corresponding to a certain pathogenic microorganism type in the current period is larger, the disease is more likely to be the disease source causing the childhood infectious disease epidemic in the current period.
Considering that in actual situations, a certain pathogenic microorganism type may present more diseased children than other pathogenic microorganism types in normal situations, in order to avoid mistaking pathogenic microorganism types which do not cause the epidemic of childhood infectious diseases for disease sources causing the epidemic of childhood infectious diseases, the embodiment further combines the difference between the number of diseased children corresponding to each pathogenic microorganism type in the current time period and the number of diseased children corresponding to the historical time period, and more accurately analyzes the pathogenic microorganism types which may cause the epidemic of childhood infectious diseases in the current time period.
Therefore, according to the method, the target microorganism type with prominent pathogenicity is screened according to the difference of the number of sick children corresponding to each pathogenic microorganism type in the current time period and the number of sick children corresponding to the historical time period, so that the epidemic situation of the children infectious diseases at the current moment can be accurately and efficiently analyzed later. Note that, in this embodiment, the duration of the setting history period is 30 days, and the duration of the setting history period may be set by the practitioner according to the actual situation, which is not limited herein. It should be noted that the ending time of the historical time period must be the initial time of the current time period, and at the same time, the sick child medical records of pediatric at least two months are already recorded in the database of the hospital.
In one implementation manner of this embodiment, referring to fig. 2, a flowchart of a method for obtaining a target microorganism type according to this embodiment is shown, where the method includes the following steps:
Step S201, obtaining the prominence degree of each pathogenic microorganism type according to the corresponding diseased child ratio of each pathogenic microorganism type in the current time period and the difference of the corresponding diseased child ratio in the historical time period.
When a certain pathogenic microorganism type corresponds to a larger proportion of sick children in the current period of time, it is stated that the pathogenic microorganism type is more likely to be the main disease source of the sick children in the current period of time. Meanwhile, when the ratio of the sick children corresponding to the pathogenic microorganism type in the current time period is larger than that of the sick children corresponding to the historical time period, the pathogenic microorganism type is more likely to be the main disease source of the sick children in the current time period. Furthermore, the embodiment obtains the protruding degree of each pathogenic microorganism type according to the corresponding diseased child ratio of each pathogenic microorganism type in the current time period and the difference of the corresponding diseased child ratio in the historical time period. The greater the degree of prominence, the more likely the corresponding pathogenic microorganism type is the primary source of disease for the child suffering from the disease during the current time period.
In one implementation manner of the embodiment, the method for obtaining the salient degree is that for any pathogenic microorganism type, the ratio of the number of diseased children corresponding to the pathogenic microorganism type in the current time period to the number of all diseased children in the current time period is obtained to serve as a first reference value, the larger the first reference value is, the more likely the pathogenic microorganism type is to be the focus disease source of the diseased children in the current time period, in order to analyze whether the pathogenic microorganism type is the focus disease source of the diseased children in the current time period more accurately, the ratio of the number of the diseased children corresponding to the pathogenic microorganism type in the historical time period to the number of all diseased children in the historical time period is further obtained to serve as a second reference value, when the first reference value is obviously larger than the second reference value, the more accurate description is that the pathogenic microorganism type is the focus disease source of the diseased children in the current time period, the result of normalization is carried out on the first reference value and the second reference value is used as an adjustment weight, and the larger the first reference value is more accurate the reference value is, so that the product of the first reference value and the pathogenic microorganism type is used as the salient degree of the pathogenic microorganism type.
Wherein, the calculation formula of the degree of prominence is: In the formula (I), in the formula (II), A degree of prominence for the ith pathogenic microorganism type; the number of the sick children corresponding to the ith pathogenic microorganism type in the current time period is N, wherein N is the number of all the sick children in the current time period; Is a first reference value; A number of sick children corresponding to the ith pathogenic microorganism type over a historical period of time; for all sick children in a historical period of time; Is a second reference value; To adjust the weights.
To this end, the degree of prominence for each pathogenic microorganism type is obtained.
Step S202, taking the pathogenic microorganism type corresponding to the maximum degree of protrusion as the target microorganism type.
The greater the degree of protrusion, the more likely the corresponding pathogenic microorganism type is the main disease source of the sick children in the current time period, and further the pathogenic microorganism type corresponding to the greatest degree of protrusion is taken as the target microorganism type in the embodiment. When at least two pathogenic microorganism types corresponding to the maximum protruding degree exist, the number of diseased children corresponding to each pathogenic microorganism type corresponding to the maximum protruding degree in the current time period is obtained and used as the first number, and the pathogenic microorganism type corresponding to the maximum first number is used as the target microorganism type.
And step S3, taking all the sick children corresponding to the target microorganism type in the current time period as target children, taking all the assay data of the target children which are higher as target data, and acquiring the epidemic degree of the children infectious diseases at the current moment according to the change condition of the target children in the current time period and the occurrence condition of each target data in the target children.
Specifically, when the childhood infectious disease occurs, the pediatric clinic can have the situation that the number of sick children corresponding to the target microorganism type increases rapidly in a short period, particularly, the number of sick children corresponding to the target microorganism type can be in two distinct states before and after a time node when the childhood infectious disease occurs, and in order to better describe, the embodiment takes the sick children corresponding to the target microorganism type in the current time period as the target children, and further analyzes the prevalence degree of the childhood infectious disease at the current moment according to the change condition of the target children in the current time period.
In consideration of the difference of the target children due to the self state, the condition symptoms of different target children can be different, but the change of the test data of the target children should be consistent, because the etiology of the target children is the same and all are caused by the target microorganism type. It is known that when certain test data deviate from the corresponding normal range, the test data are abnormal, in order to further determine the epidemic accuracy of the childhood infectious diseases at the current time of analysis, the test data with higher target childhood are all taken as target data, namely, the test data higher than the normal range in the test data of the target childhood are all taken as target data, then the occurrence condition of each target data in the target childhood is analyzed, and when the ratio of the target data in the target childhood is larger, the epidemic condition of the childhood infectious diseases in the current time period of analysis is more accurate. Therefore, according to the embodiment, the epidemic degree of the child infectious diseases at the current moment is obtained according to the change condition of the target child in the current time period and the occurrence condition of each target data in the target child. The higher the popularity, the more the early warning, prevention and control of the children infectious diseases are required at the current moment, and the further spread of the children infectious diseases is avoided.
Preferably, in one implementation manner of this embodiment, referring to fig. 3, a flowchart of a popularity obtaining method provided by this embodiment is shown, where the method includes the following steps:
Step S301, according to the change condition of the target child in the current time period, the epidemic trend degree of the child infectious disease at the current moment is obtained.
The higher the epidemic tendency degree is, the more serious the epidemic of the children infectious diseases is at the current moment, and early warning is needed, so that the children infectious diseases can be timely prevented and controlled.
The method for acquiring the popularity tendency degree comprises the steps of firstly uniformly dividing a current time period into local time periods, then acquiring the number of target children in each local time period as a reference number, so that the change condition of the target children in the current time period can be accurately analyzed later, setting the duration of the local time period to be 1 day (24 hours), and setting the size of the local time period according to actual conditions by an implementer without limitation. As known, when the childhood infectious disease flows, the reference number will increase suddenly, so according to the variation condition of the reference number, the embodiment obtains the potential disease stage and the epidemic disease stage in the current time period, so that the epidemic condition of the childhood infectious disease in the current time period is accurately analyzed later;
The method for acquiring the potential disease stage and the epidemic disease stage comprises the steps of acquiring a difference value of a reference number of each local time period and a previous adjacent local time period as a first value of each local time period, wherein the first local time period does not exist in the previous adjacent local time period, so that the first local time period in the current time period is not analyzed, the local time period corresponding to the largest first value is taken as a segmentation time period, then the time period corresponding to all the segmentation time periods before the segmentation time period is taken as the potential disease stage, and the time period corresponding to all the local time periods after the segmentation time period is taken as the epidemic disease stage. When the maximum first value corresponds to a plurality of local time periods, the local time period corresponding to the maximum first value that appears for the first time is used as the divided time period.
The method comprises the steps of analyzing the epidemic situation of the child infectious disease in a current time period, taking the maximum reference quantity in a potential disease stage as a potential representative quantity, taking the local time periods in the disease epidemic stage as analysis time periods, obtaining the ratio of the reference quantity to the potential representative quantity of the analysis time periods as a disease epidemic analysis value of the analysis time periods for any analysis time period, wherein the larger the disease epidemic analysis value is, the more serious the epidemic of the child infectious disease represented by the analysis time period is, the more accurately represents the epidemic situation of the child infectious disease corresponding to the analysis time period, further obtaining the ratio of the first value of the analysis time period to the reference quantity of the previous adjacent local time period of the analysis time period as a reference weight of the analysis time period, the more serious the child infectious disease represented by the analysis time period is, and further taking the product of the disease epidemic analysis value and the reference weight as a local disease epidemic reference value of the analysis time period. In order to integrally analyze the epidemic situation of the children infectious diseases in the current time period, namely, the epidemic situation of the children infectious diseases at the current time is determined, and then the result of normalizing the average value of the local disease epidemic reference values in all analysis time periods is used as the epidemic tendency degree of the children infectious diseases at the current time.
The calculation formula of the popularity tendency degree is as follows: Wherein W is the epidemic tendency degree of the childhood infectious diseases at the current moment, J is the number of analysis time periods; A reference number for the j-th analysis period; Is a potential representative number; disease prevalence analysis value for the j-th analysis period; A reference number for the j-1 th analysis period; a first value for a j-th analysis period; Reference weights for the j-th analysis period; For the j-th analysis period, norm is a normalization function. It should be noted that the number of the substrates, when j is a number of times 1, Is the reference number of segments.
And step S302, obtaining the disease assay similarity degree of the target microorganism type at the current moment according to the occurrence ratio of each target data in the target children.
When each kind of target data appears in each kind of target children, the more accurate the epidemic tendency degree of the children infectious diseases under the current time of analysis is explained, and then the disease test similarity degree of the target microorganism type under the current time is obtained according to the appearance ratio of each kind of target data in the target children. The greater the similarity of the disease assays, the more accurate the prevalence of childhood infectious disease at the current time.
In one implementation manner of the embodiment, the method for acquiring the disease assay similarity includes taking the ratio of the number of target children containing the target data to the number of all target children as the duty ratio of the target data, and taking the addition result of the duty ratios of all target data as the disease assay similarity of the target microorganism type at the current moment.
Step S303, the product of the epidemic tendency degree and the disease test similarity degree is normalized to be used as the epidemic degree of the children infectious diseases at the current moment.
The greater the degree of prevalence is known, the more severe the prevalence of childhood infectious disease at the current time; the disease test similarity is larger, the epidemic tendency is more accurate, and the product of the epidemic tendency and the disease test similarity is normalized to be used as the epidemic degree of the childhood infectious diseases at the current moment in order to accurately represent the epidemic situation of the childhood infectious diseases at the current moment. In this example, the product of the degree of epidemic tendency and the degree of similarity of the disease assay is normalized by a norm normalization function.
And step S4, judging whether early warning, prevention and control of the children infectious diseases are carried out at the current moment based on the popularity.
The higher the known popularity degree is, the more the early warning of the children infectious diseases is required to be sent out at the current moment, so that the children infectious diseases are timely prevented and controlled, and the further spread of the children infectious diseases is avoided. Therefore, the embodiment judges whether early warning and prevention and control of the childhood infectious diseases are performed at the current moment based on the popularity.
Preferably, in one implementation manner of the embodiment, the method for judging whether early warning and prevention and control of the child infectious disease is performed at the current moment based on the popularity degree includes that the preset popularity degree threshold value is set to be 0.42, and an implementer can set the magnitude of the preset popularity degree threshold value according to actual conditions without limitation; when the popularity is greater than a preset popularity threshold, early warning and prevention and control of the child infectious diseases are required at the current moment, namely, a real-time early warning panel of a doctor terminal can send out early warning of the child infectious diseases at the current moment, and synchronously submit a popularity trend report to a disease control center to remind the current need of prevention and control of the child infectious diseases, provide prevention and control suggestions for schools, parents and medical institutions in advance, and prepare corresponding prevention and control resources (such as vaccines, medicines and medical facilities) so as to effectively reduce the transmission risk of the child infectious diseases while improving the capability of early identifying the child infectious diseases;
when the popularity is smaller than or equal to the preset popularity threshold, early warning and prevention and control of the children infectious diseases are not needed at the current moment.
In summary, the embodiment obtains the pathogenic microorganism type and the assay data of the sick children in the current time period, screens out the target microorganism type according to the sick children corresponding to the pathogenic microorganism type in the current time period and the sick children corresponding to the historical time period, takes the sick children corresponding to the target microorganism type as the target children, takes the assay data of the target children with higher height as the target data, and obtains the epidemic degree of the children infectious diseases at the current moment according to the change condition of the target children and the occurrence condition of the target data to judge whether early warning and prevention and control of the children infectious diseases are carried out. According to the invention, the popularity of the children infectious diseases is accurately obtained in real time, so that early warning, prevention and control are more accurately and timely carried out, and the situations of delay diagnosis and delayed prevention and control reaction of the children infectious diseases are effectively reduced.
Example 2:
The invention also provides an early warning and prevention and control system for the infectious diseases of children based on artificial intelligence, referring to fig. 4, which shows a structural diagram of the early warning and prevention and control system for the infectious diseases of children based on artificial intelligence, provided by an embodiment of the invention, the system comprises a data acquisition module 10, a target microorganism type acquisition module 20, a popularity acquisition module 30 and a data processing module 40.
The data acquisition module 10 is used for acquiring an electronic medical record of each sick child in the current time period, wherein the electronic medical record contains pathogenic microorganism types and various assay data.
The target microorganism type acquisition module 20 is used for screening out target microorganism types with prominent pathogenicity according to the number of sick children corresponding to each pathogenic microorganism type in the current time period and the difference of the number of sick children corresponding to the historical time period.
The popularity obtaining module 30 is configured to obtain popularity of the infectious disease of the child at the current moment according to a change condition of the target child in the current time period and an occurrence condition of each target data in the target child, wherein the popularity obtaining module is configured to take all diseased children corresponding to the target microorganism type in the current time period as target children, take all assay data of the target child which is higher as target data, and obtain popularity of the infectious disease of the child at the current time.
The data processing module 40 is configured to determine whether early warning and prevention and control of the childhood infectious disease are performed at the current time based on the popularity.
It should be noted that, in the system provided in the above embodiment, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the computer device is divided into different functional modules to perform all or part of the functions described above. In addition, the early warning and prevention and control system for the infectious diseases of the children based on the artificial intelligence provided in the above embodiment belongs to the same concept as the early warning and prevention and control method embodiment for the infectious diseases of the children based on the artificial intelligence, and the detailed implementation process of the early warning and prevention and control system is shown in the method embodiment and will not be described herein.
Example 3:
The application also provides an early warning and prevention and control device for the child infectious diseases based on artificial intelligence, which comprises a memory and a processor, wherein executable program codes are stored in the memory, and the processor is used for calling and executing the executable program codes to execute the early warning and prevention and control method for the child infectious diseases based on the artificial intelligence. The device can be a chip, a component or a module, the chip can comprise a processor and a memory which are connected, wherein the memory is used for storing instructions, and when the processor calls and executes the instructions, the chip can execute the early warning and prevention and control method for the child infectious diseases based on the artificial intelligence.
In addition, referring to fig. 5, the embodiment of the present application further protects a computer device, where the computer device includes a memory 401, a processor 402, and a computer program 403 stored in the memory 401 and running on the processor 402, where the processor 402 executes the computer program 403, so that the computer device can execute any of the early warning and prevention methods for childhood infectious diseases based on artificial intelligence described above.
Example 4:
The embodiment also provides a computer readable storage medium, in which computer program code is stored, when the computer program code runs on a computer, the computer is caused to execute the related method steps to implement the early warning and prevention and control method for the child infectious diseases based on artificial intelligence provided by the embodiment.
Example 5:
The embodiment also provides a computer program product, when the computer program product runs on a computer, the computer is caused to execute the related steps so as to realize the early warning and prevention and control method for the child infectious diseases based on the artificial intelligence.
The apparatus, the computer readable storage medium, the computer program product, or the chip provided in this embodiment are used to execute the corresponding method provided above, and therefore, the advantages achieved by the apparatus, the computer readable storage medium, the computer program product, or the chip can refer to the advantages of the corresponding method provided above, which are not described herein.
It should be noted that the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
Claims (5)
1. The early warning and prevention and control system for the infectious diseases of children based on artificial intelligence is characterized by comprising a data acquisition module, a target microorganism type acquisition module, a popularity acquisition module and a data processing module:
the data acquisition module is used for acquiring an electronic medical record of each sick child in the current time period, wherein the electronic medical record comprises pathogenic microorganism types and various assay data;
the target microorganism type acquisition module is used for screening out target microorganism types with prominent pathogenicity according to the number of sick children corresponding to each pathogenic microorganism type in the current time period and the difference of the number of sick children corresponding to the historical time period;
The popularity acquisition module is used for taking all sick children corresponding to the target microorganism type in the current time period as target children, taking assay data of the target children which are higher as target data, and acquiring the popularity of the children infectious diseases at the current moment according to the change condition of the target children in the current time period and the occurrence condition of each target data in the target children;
The data processing module is used for judging whether early warning and prevention and control of the children infectious diseases are carried out at the current moment based on the popularity;
The method for acquiring the target microorganism type comprises the following steps:
Obtaining the prominence degree of each pathogenic microorganism type according to the corresponding diseased child ratio of each pathogenic microorganism type in the current time period and the difference of the corresponding diseased child ratio in the historical time period;
taking the pathogenic microorganism type corresponding to the maximum degree of protrusion as a target microorganism type;
when at least two pathogenic microorganism types corresponding to the maximum protruding degree exist, obtaining the number of diseased children corresponding to each pathogenic microorganism type corresponding to the maximum protruding degree in the current time period as a first number;
Taking the maximum first number of corresponding pathogenic microorganism types as target microorganism types;
the method for obtaining the protruding degree comprises the following steps:
For any pathogenic microorganism type, obtaining the ratio of the number of the sick children corresponding to the pathogenic microorganism type in the current time period to the number of all the sick children in the current time period as a first reference value;
acquiring the ratio of the number of the sick children corresponding to the pathogenic microorganism type in the historical time period to the number of all the sick children in the historical time period as a second reference value;
normalizing the difference value between the first reference value and the second reference value to obtain an adjustment weight;
taking the product of the adjustment weight and the first reference value as the degree of prominence of the pathogenic microorganism type;
The calculation formula of the degree of protrusion is:
;
In the formula, A degree of prominence for the ith pathogenic microorganism type; the number of the sick children corresponding to the ith pathogenic microorganism type in the current time period is N, wherein N is the number of all the sick children in the current time period; Is a first reference value; A number of sick children corresponding to the ith pathogenic microorganism type over a historical period of time; for all sick children in a historical period of time; Is a second reference value; to adjust the weight;
The popularity obtaining method comprises the following steps:
According to the change condition of the target child in the current time period, obtaining the epidemic tendency degree of the child infectious disease at the current moment;
Obtaining the disease assay similarity of the target microorganism type at the current moment according to the occurrence ratio of each target data in the target children;
the product of the epidemic tendency degree and the disease test similarity degree is normalized to be used as the epidemic degree of the children infectious diseases at the current moment;
the acquisition method of the popularity tendency degree comprises the following steps:
Uniformly dividing the current time period into local time periods, and acquiring the number of target children in each local time period as a reference number;
acquiring a potential disease stage and a epidemic disease stage in the current time period according to the change condition of the reference quantity;
taking the maximum reference number in the potential disease stage as the potential representative number, and taking the local time periods in the disease epidemic stage as the analysis time periods;
for any analysis period, taking the ratio of the reference number to the potential representative number of the analysis period as a disease prevalence analysis value of the analysis period;
Taking the difference value of the reference number of the analysis time period and the previous adjacent local time period as a first value of the analysis time period;
Taking the ratio of the first value to the reference number of the adjacent local time period before the analysis time period as the reference weight of the analysis time period;
taking the product of the disease prevalence analysis value and the reference weight as a local disease prevalence reference value for the analysis period;
The average value of the local disease epidemic reference values in all analysis time periods is normalized to be used as the epidemic tendency degree of the children infectious diseases at the current moment;
the calculation formula of the popularity tendency degree is as follows: Wherein W is the epidemic tendency degree of the childhood infectious diseases at the current moment, J is the number of analysis time periods; A reference number for the j-th analysis period; Is a potential representative number; disease prevalence analysis value for the j-th analysis period; A reference number for the j-1 th analysis period; a first value for a j-th analysis period; Reference weights for the j-th analysis period; for the local disease prevalence reference value of the j-th analysis period, norm is a normalization function, it is noted that when j is 1, Is the reference number of segments.
2. The early warning and prevention and control system for childhood infectious diseases based on artificial intelligence of claim 1, wherein the method for acquiring the potential disease stage and the epidemic disease stage in the current time period is as follows:
Acquiring a first value of each local time period, taking the local time period corresponding to the maximum first value as a segmentation time period, and taking the time periods corresponding to the segmentation time period and all the previous local time periods as potential stages of the disease;
The time period corresponding to all the local time periods after the divided time period is taken as the disease epidemic stage.
3. The early warning and prevention and control system for childhood infectious diseases based on artificial intelligence of claim 2, wherein when the maximum first value corresponds to a plurality of local time periods, the local time period corresponding to the maximum first value appearing first is taken as the divided time period.
4. The early warning and prevention and control system for childhood infectious diseases based on artificial intelligence as defined in claim 1, wherein the method for obtaining the similarity of the disease assay is as follows:
For any target data, taking the ratio of the number of target children containing the target data to the number of all target children as the duty ratio degree of the target data;
and taking the addition result of the duty ratio degree of all the target data as the disease test similarity degree of the target microorganism type at the current moment.
5. The early warning and prevention and control system for the infectious diseases of children based on artificial intelligence as set forth in claim 1, wherein the method for judging whether the early warning and prevention and control of the infectious diseases of children is performed at the current moment based on the popularity degree is as follows:
When the popularity is greater than a preset popularity threshold, early warning and prevention and control of the children infectious diseases are required at the current moment;
When the popularity is smaller than or equal to a preset popularity threshold value, early warning and prevention and control of the children infectious diseases are not needed at the current moment.
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