CN111834005B - Method, device, medium and equipment for screening medical data based on infectious diseases - Google Patents
Method, device, medium and equipment for screening medical data based on infectious diseases Download PDFInfo
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
Abstract
The embodiment of the invention relates to a method, a device, a medium and equipment for screening medical data based on infectious diseases, which relate to the technical field of medical big data processing, and the method comprises the following steps: receiving a plurality of data screening requests input by a user side according to screening conditions; wherein the screening condition is symptom information corresponding to the infectious disease; responding to each data screening request, and matching a decision tree corresponding to each screening request from a clinical decision support system; and searching the decision tree layer by layer, determining leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes from the decision tree, and sending the predicted values to the user side. The embodiment of the invention improves the screening efficiency of the patients with infectious diseases.
Description
Technical Field
The embodiment of the invention relates to the technical field of medical big data processing, in particular to a method for screening medical data based on infectious diseases, a device for screening medical data based on infectious diseases, a system for screening medical data based on infectious diseases, a computer-readable storage medium and electronic equipment.
Background
Infectious diseases cause serious harm to the harmony and stability of the society and the safety of lives and properties of people, and also bring unprecedented pressure and challenge to the traditional medical system. Therefore, how to make full use of computer technology for scientific prevention and treatment helps decision makers to make precise measures and relieve hospital pressure becomes a difficult problem to be solved urgently at present.
In the prior art, screening of patients with infectious diseases is mostly performed by the following methods: medical personnel screen populations for the presence of infectious disease patients through a number of basic tests (e.g., body temperature measurement, medical history and symptoms interrogation, etc.).
However, the above method has the following drawbacks: on one hand, because medical staff are required to carry out manual detection, the screening efficiency of infectious disease patients is lower; on the other hand, due to the limitation of the number of medical staff, all people cannot be screened in time, and the screening timeliness is lower.
Therefore, there is a need to provide a new method for screening medical data based on infectious diseases.
It is to be noted that the information invented in the above background section is only for enhancing the understanding of the background of the present invention, and therefore, may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
An object of the present invention is to provide an infectious disease-based medical data screening method, an infectious disease-based medical data screening apparatus, an infectious disease-based medical data screening system, a computer-readable storage medium, and an electronic device, thereby overcoming, at least to some extent, the problem of low screening efficiency due to limitations and disadvantages of the related art.
According to one aspect of the present disclosure, there is provided a method for screening medical data based on infectious diseases, comprising:
receiving a plurality of data screening requests input by a user side according to screening conditions; wherein the screening condition is symptom information corresponding to the infectious disease;
responding to each data screening request, and matching a decision tree corresponding to each screening request from a clinical decision support system;
and searching the decision tree layer by layer, determining leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes from the decision tree, and sending the predicted values to the user side.
In an exemplary embodiment of the present disclosure, the decision tree is determined by:
standardizing the medical guideline to obtain a medical knowledge screening library corresponding to the infectious disease;
extracting a root node and a child node corresponding to the root node from the medical knowledge screening library according to the sequence of the occurrence of the symptom information of the infectious disease;
and generating the decision tree according to the root node and the child nodes corresponding to the root node, and storing the decision tree into a clinical decision support system.
In an exemplary embodiment of the present disclosure, standardizing the medical guideline to obtain the medical knowledge screening library corresponding to the infectious disease includes:
standardizing specific fields in the medical guide to obtain standardized results of the specific fields; wherein the specific field is symptom information of infectious disease;
and obtaining a medical knowledge screening library corresponding to the infectious diseases according to the standardized result of the specific field.
In an exemplary embodiment of the present disclosure, the method for screening medical data based on infectious disease further includes:
counting the predicted value, and predicting the number of infectious diseases according to the counting result;
optimizing the decision tree based on an actual population of infectious disease and a predicted population of infectious disease.
In an exemplary embodiment of the present disclosure, optimizing the decision tree based on the actual population of infectious diseases and the predicted population of infectious diseases comprises:
constructing a loss function based on the actual infectious population of the infectious disease and the predicted infectious population, and judging whether the function value of the loss function is greater than a preset threshold value;
and when the function value of the loss function is judged to be larger than the preset threshold value, adjusting the decision tree until the function value of the loss function is not larger than the preset threshold value.
In an exemplary embodiment of the present disclosure, the method for screening medical data based on infectious disease further includes:
and matching a recommended diagnosis and treatment scheme corresponding to the predicted value from the clinical decision support system, and sending the recommended diagnosis and treatment scheme to the user side.
According to an aspect of the present disclosure, there is provided an infectious disease-based medical data screening apparatus including:
the receiving module is used for receiving a plurality of data screening requests input by the user side according to the screening conditions; wherein the screening condition is symptom information corresponding to the infectious disease;
a matching module for responding each data screening request and matching a decision tree corresponding to each screening request from a clinical decision support system;
and the searching module is used for searching the decision tree layer by layer, determining the leaf nodes corresponding to the data screening requests and the predicted values corresponding to the leaf nodes from the decision tree, and sending the predicted values to the user side.
According to an aspect of the present disclosure, there is provided an infectious disease-based medical data screening system, including:
the system comprises a user side, a server and a data screening request sending module, wherein the user side is used for receiving screening conditions input by a user, generating a data screening request according to the screening conditions and sending the data screening request to the server;
the server is connected with the user side network and is used for realizing any infectious disease-based medical data screening method;
and the clinical decision support system is arranged in the server and used for storing the decision tree.
According to an aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the infectious disease-based medical data screening method of any one of the above.
According to an aspect of the present disclosure, there is provided an electronic device including:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform any of the infectious disease-based medical data screening methods described above via execution of the executable instructions.
According to the infectious disease-based medical data screening method provided by the embodiment of the invention, on one hand, a plurality of data screening requests input by a user side according to screening conditions are received; then responding to each data screening request, and matching a decision tree corresponding to each screening request from a clinical decision support system; finally, the decision tree is searched layer by layer, leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes are determined from the decision tree, and the predicted values are sent to a user side, so that a user can directly judge whether the patient is an infectious disease patient according to the predicted values, and the problem that in the prior art, medical staff are required to perform manual detection, and then the infectious disease patient screening efficiency is low is solved; on the other hand, the problem that all people cannot be screened in time due to the limitation of the number of medical staff in the prior art, so that the screening timeliness is low is solved, and the screening efficiency is improved; on the other hand, the decision tree is searched layer by layer, the leaf nodes corresponding to the data screening requests and the predicted values corresponding to the leaf nodes are determined from the decision tree, and the predicted values are sent to the user side, so that the user can select corresponding treatment measures according to the predicted values, the timeliness of discovery is improved, and the user experience is further improved; further, matching decision trees corresponding to the screening conditions from the clinical decision support system; and then searching the decision tree layer by layer, determining leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes from the decision tree, so that the searching efficiency of the predicted values is improved, and meanwhile, the decision tree is matched from a clinical decision support system, so that the pressure of a server is reduced.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
Fig. 1 schematically shows a flow chart of a method for infectious disease based medical data screening according to an exemplary embodiment of the present invention.
FIG. 2 schematically illustrates a block diagram of an infectious disease-based medical data screening system, according to an example embodiment of the present invention.
Fig. 3 schematically shows a flow chart of a method for constructing a decision tree according to an exemplary embodiment of the present invention.
Fig. 4 schematically shows an example diagram of a decision tree according to an example embodiment of the invention.
Fig. 5 schematically shows a flow chart of another method for infectious disease based medical data screening according to an exemplary embodiment of the present invention.
Fig. 6 schematically illustrates a block diagram of an infectious disease-based medical data screening apparatus according to an exemplary embodiment of the present invention.
Fig. 7 schematically illustrates an electronic device for implementing the above-described infectious disease-based medical data screening method according to an exemplary embodiment of the present invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the invention.
Furthermore, the drawings are merely schematic illustrations of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The example embodiment first provides a method for screening medical data based on infectious diseases, which can be operated in a server, a server cluster or a cloud server; of course, those skilled in the art may also operate the method of the present invention on other platforms as needed, and this is not particularly limited in this exemplary embodiment. Referring to fig. 1, the infectious disease-based medical data screening method may include the steps of:
s110, receiving a plurality of data screening requests input by a user side according to screening conditions; wherein the screening condition is symptom information corresponding to the infectious disease;
s120, responding to each data screening request, and matching a decision tree corresponding to each screening request from a clinical decision support system;
step S130, searching the decision tree layer by layer, determining leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes from the decision tree, and sending the predicted values to the user side.
In the method for screening medical data based on infectious diseases, on one hand, a plurality of data screening requests input by a user side according to screening conditions are received; then responding to each data screening request, and matching a decision tree corresponding to each screening request from a clinical decision support system; finally, the decision tree is searched layer by layer, leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes are determined from the decision tree, and the predicted values are sent to a user side, so that a user can directly judge whether the patient is an infectious disease patient according to the predicted values, the problem that in the prior art, medical staff are required to perform manual detection, the infectious disease patient screening efficiency is low is solved, and the screening efficiency is improved; on the other hand, the problem that all people cannot be screened in time due to the limitation of the number of medical care personnel in the prior art, and the screening timeliness is low is solved; on the other hand, the decision tree is searched layer by layer, the leaf nodes corresponding to the data screening requests and the predicted values corresponding to the leaf nodes are determined from the decision tree, and the predicted values are sent to the user side, so that the user can select corresponding treatment measures according to the predicted values, the timeliness of discovery is improved, and the user experience is further improved; further, matching decision trees corresponding to the screening conditions from the clinical decision support system; and then searching the decision tree layer by layer, determining leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes from the decision tree, so that the searching efficiency of the predicted values is improved, and meanwhile, the decision tree is matched from a clinical decision support system, so that the pressure of a server is reduced.
Hereinafter, steps included in the infectious disease-based medical data screening method according to the exemplary embodiment of the present invention will be explained and explained in detail with reference to the accompanying drawings.
First, terms related to exemplary embodiments of the present invention are explained and explained.
The CDSS (Clinical Decision Support System) generally refers to a computer System capable of providing Support for Clinical Decision, and the System fully utilizes available and suitable computer technology, and improves and enhances Decision efficiency by a man-machine interaction mode for semi-structured or unstructured medical problems.
Medical guidelines, the revised guidelines of the world health organization for global monitoring of infectious diseases, with monitoring goals being: monitoring interpersonal transmission trends, rapidly discovering new cases emerging from countries with virus epidemics, providing epidemiological information for national, regional, and global risk assessment, and providing epidemiological information for guidance and response measures.
ICD-10, International Classification of Diseases, is an International unified disease Classification method established by WHO, classifying Diseases into an ordered combination according to the characteristics of disease causes, pathology, clinical manifestation, anatomical location and the like, and expressing the disease by a coding method. It is common worldwide to revise the 10 th international statistical classification of diseases and related health problems, which retains the ICD abbreviation and is collectively referred to as ICD-10.
Next, an infectious disease-based medical data screening system according to an exemplary embodiment of the present invention will be explained and explained. Referring to fig. 2, the infectious disease-based medical data screening system may include a user terminal 200, a server 210, and a clinical decision support system 220. Wherein:
the user side can be used for receiving the screening conditions, generating a data screening request according to the screening conditions and sending the data screening request to the server by the user side;
the server is connected with the user side network and used for realizing the infectious disease-based medical data screening method in the embodiment of the invention;
and the clinical decision support system is arranged in the server and used for storing the decision tree.
Further, the user terminal 200 may comprise one or more of 201, 202 and 203 shown in fig. 2, and the user terminal is connected to the server terminal through a network, and the server terminal is connected to the clinical decision support system through the network, wherein the network may comprise various connection types, such as wired, wireless communication links, or fiber optic cables. It should be added that the number of the user terminals and the servers in fig. 2 is only schematic. There may be any number of clients and servers, as desired for implementation. For example, server 210 may be a server cluster comprising a plurality of servers, and the like.
The user can use the user terminals 201, 202 and 203 to interact with the server 210 through the network to input the filtering conditions and receive the predicted values, etc. The user terminals 201, 202, and 203 may be various electronic devices having a display screen, including but not limited to smart phones, tablet computers, portable computers, desktop computers, and the like.
Further, the decision tree according to the exemplary embodiment of the present invention is explained and illustrated. Referring to fig. 3, the decision tree is obtained by:
in step S310, a medical guideline is standardized to obtain a medical knowledge screening library corresponding to the infectious disease;
in this exemplary embodiment, first, a specific field in the medical guideline is normalized to obtain a normalized result of the specific field; wherein the specific field is symptom information of infectious disease; and secondly, obtaining a medical knowledge screening library corresponding to the infectious disease according to the standardized result of the specific field.
In step S320, extracting a root node and child nodes corresponding to the root node from the medical knowledge screening library according to a sequence of occurrence of the symptom information of the infectious disease;
in step S330, the decision tree is generated according to the root node and the child nodes corresponding to the root node, and the decision tree is stored in a clinical decision support system.
Hereinafter, steps S310 to S330 and the steps involved therein will be explained and explained. Firstly, standardizing a specific field in the medical guideline to obtain a standardized result of the specific field; wherein the specific field is the symptom information of the infectious disease. For example, the ICD-10 standardizes a specific field in the medical guideline to obtain a standardized result of the specific field, so that the medical guideline can be standardized in a full scale, and the defect that only local data can be provided for standardization in the related art can be overcome to a certain extent.
And then, based on the standardized result according to the specific field, obtaining a medical knowledge screening library corresponding to the infectious disease. Wherein, the medical knowledge screening library comprises the specific fields and the standardized results of the specific fields. Specifically, after the specific field is standardized, a medical knowledge screening library may be generated based on the standardized result of the specific field. For example, after "fever" is normalized, the normalized result obtained is "fever".
Further, the root node and the child nodes corresponding to the root node can be extracted from the medical knowledge screening library according to the sequence of the occurrence of the symptom information of the infectious disease. Specifically, the root node may be fever, for example, and if there is a fever symptom, the child nodes corresponding to the fever symptom may include fever temperature, fever duration, a history of chronic diseases, an epidemiological history, and the like; if fever symptoms are not present, the child nodes corresponding to the fever symptoms may include a history of chronic illness, other symptoms, epidemiological history, and the like.
Finally, after the root node and the child node corresponding to the root node are obtained, a decision tree may be generated based on each root node and the corresponding child node, which may specifically refer to fig. 4; the decision tree is then stored in a clinical decision support system for subsequent matching.
Specifically, in fig. 4, the root node includes whether to generate heat, and if so, the child node corresponding to the heat-generating branch includes: body temperature, duration of fever, chronic disease history and epidemiological history, if there is epidemiological history, then it can be judged as a suspected case, if there is no epidemiological history, then its corresponding branch is whether there is symptoms of high fever/middle low fever 3 days/dyspnea/chest pain, if there is, then the predicted value is an urgent symptom, if there is not, then the predicted value is a suspected symptom.
Further, if not, the child node corresponding to the branch that does not generate heat includes: the patient has a chronic disease history and other symptoms, if other symptoms exist, whether the patient has an epidemiological history is judged, if yes, the predicted value is a suspected symptom, if not, whether the patient has symptoms of dyspnea/chest pain is judged, if yes, the predicted value is an urgent symptom, if not, whether the patient has main symptoms is judged, if yes, the predicted value is a suspected symptom, and if not, the predicted value is a rare suspected symptom; and if no other symptoms exist, judging whether the epidemiological history exists, if so, judging that the predicted value is a suspected symptom, and if not, judging that the predicted value is normal.
It should be added that, when a change in the medical guideline is detected, the medical knowledge screening library and the decision tree are updated based on the changed medical guideline, so that the medical knowledge screening library and the decision tree have high timeliness, and the accuracy of the inference conclusion is ensured.
Hereinafter, steps S110 to S130 will be explained and explained.
In step S110, a plurality of data filtering requests input by the user side according to the filtering condition are received; wherein the screening condition is symptom information corresponding to the infectious disease.
Specifically, a plurality of data screening requests input by a user through a user side according to screening conditions can be received; specifically, a user can input a plurality of data screening requests through screening conditions provided by a display interface of an application program provided by a user side; for example, the screening conditions may include: whether there are fever symptoms, duration of fever, history of chronic illness, epidemiological history, etc.; of course, other symptoms may be used as the screening condition based on the actual situation, and this example is not limited to this.
In step S120, in response to each of the data screening requests, a decision tree corresponding to each of the screening requests is matched from the clinical decision support system.
For example, when the data screening request includes a fever symptom, a decision tree having a branch with a fever symptom may be directly matched from the clinical decision support system, and when there is no fever symptom, a decision tree having a branch without a fever symptom may be directly matched; further, when the data screening request includes a branch with a slow medical history and other symptoms, the branch with other symptoms can be continuously matched; finally, when the data screening request includes a symptom that does not have an epidemiological history but has dyspnea/chest pain, then the final matching decision tree is: no fever, a history of slow disease, other symptoms, no epidemiological history, a decision tree of dyspnea/chest pain. It should be added that, since the user inputs the data screening requests by means of the question answering machine provided by the application program at the user end, the decision tree corresponding to each screening request can be matched step by step according to the input of the user.
In step S130, the decision tree is searched layer by layer, a leaf node corresponding to each data screening request and a predicted value corresponding to the leaf node are determined from the decision tree, and the predicted value is sent to the user side.
In the present exemplary embodiment, after matching to a specific decision tree, the decision tree may be searched layer by layer, for example, when the decision tree with a branch of fever symptoms is matched, the leaf node corresponding to the decision tree and the predicted value corresponding to the leaf node may be determined according to the body temperature, fever duration, chronic disease history, epidemiological history and other symptoms input by the user through the user terminal, where the predicted value may include the predicted result (whether it is infected or suspected to be infected, etc.).
Further, after the prediction result is obtained, matching a recommended diagnosis and treatment scheme corresponding to the prediction value from the clinical decision support system, and sending the recommended diagnosis and treatment scheme to the user side. The recommended diagnosis and treatment plan may include, for example, a prompt visit, a household isolation observation, a medical observation, and active prevention. By the method, the user can select corresponding measures in time according to own symptoms, the timeliness of infectious disease treatment and prevention is improved, the number of infected people is reduced, and labor and time cost are saved.
FIG. 5 schematically illustrates another infectious disease-based medical data screening method according to an example embodiment of the invention. Referring to fig. 5, the method for screening medical data based on infectious diseases may further include step S510 and step S520, in which:
in step S510, counting the predicted value, and predicting the number of infectious diseases according to the counting result;
in step S520, the decision tree is optimized based on the actual population of infectious diseases and the predicted population of infectious diseases.
In the present exemplary embodiment, first, a loss function is constructed based on the actual number of persons with infectious diseases and the predicted number of persons with infectious diseases, and it is determined whether the function value of the loss function is greater than a preset threshold value; secondly, when the function value of the loss function is judged to be larger than the preset threshold value, the decision tree is adjusted until the function value of the loss function is not larger than the preset threshold value.
Hereinafter, steps S510 to S520 will be explained and explained. Firstly, counting cases with predicted values (mainly, the predicted values are infected), and then predicting the number of infectious people with infectious diseases according to the counting result; it should be added that, because there is a corresponding request ID when the screening request is sent, the corresponding patient identity can be found according to the request ID, and the actual number of infectious people can be obtained by combining the medical data information; after the predicted number of people and the actual number of people are obtained, a loss function can be constructed according to the actual number of people infected with the infection and the predicted number of people infected with the infection, wherein the loss function can be a mean square error function or a sigmoid function, or other functions, which is not limited in this example; if the loss function value is within the preset threshold value range, the accuracy of the decision tree is proved to be higher; if the loss function value is not within the preset threshold range, the decision tree can be optimized by combining the actual number of infectious people, and the screening accuracy can be further improved.
Specifically, the specific optimization process of the decision tree is explained and illustrated by taking the mean square error loss function as an example. For example, the loss function can be shown as the following equation (1):
wherein n is a statistical period, and is taken as a unit of day, and a value thereof may be 15 days or 30 days, which is not particularly limited in the exemplary embodiment of the present invention; a isiFor each day of predictionNumber of people, yiThe actual number of people per day.
Specifically, in the statistical period, the predicted number of people per day is obtained by predicting through a trained decision tree, the predicted number of people per day and the actual number of people per day are brought into the loss function, the function value is calculated, and when the value of the loss function is smaller, the result is more accurate when the number of people with infection is predicted through the decision number. Conversely, when the value of the loss function is larger, it can be determined that the number of infectious agents predicted by the decision tree is not accurate enough, and the branch content of the decision tree and/or the predicted value corresponding to the branch needs to be adjusted. For example, the reason for the large difference may be determined based on the screening condition included in each data screening request, and then the corresponding decision tree and the corresponding predicted value may be modified. Therefore, the loss function is adopted to verify the trained decision tree, so that the accuracy of the trained decision tree is improved.
Of course, when determining whether the decision tree needs to be adjusted, the threshold of the loss function may be determined according to actual experience, and when the value of the loss function obtained through the trained decision tree is verified to be smaller than the threshold through actual data, it is determined that the trained decision tree conforms to the actual application. Conversely, if the value of the penalty function is greater than the threshold, then the trained decision tree needs to be adjusted.
The embodiment of the invention also provides a medical data screening device based on the infectious diseases. Referring to fig. 6, the infectious disease-based medical data screening apparatus may include a receiving module 610, a matching module 620, and a searching module 630. Wherein:
the receiving module 610 may be configured to receive a plurality of data screening requests input by a user side according to a screening condition; wherein the screening condition is symptom information corresponding to the infectious disease;
the decision tree matching module 620 may be configured to match a decision tree corresponding to each of the screening requests from the clinical decision support system in response to each of the data screening requests;
the searching module 630 may be configured to search the decision tree layer by layer, determine a leaf node corresponding to each data screening request and a predicted value corresponding to the leaf node from the decision tree, and send the predicted value to the user side.
In an exemplary embodiment of the present disclosure, the decision tree is determined by:
standardizing the medical guideline to obtain a medical knowledge screening library corresponding to the infectious disease;
extracting a root node and a child node corresponding to the root node from the medical knowledge screening library according to the sequence of the occurrence of the symptom information of the infectious disease;
and generating the decision tree according to the root node and the child nodes corresponding to the root node, and storing the decision tree into a clinical decision support system.
In an exemplary embodiment of the present disclosure, standardizing the medical guideline to obtain the medical knowledge screening library corresponding to the infectious disease includes:
standardizing specific fields in the medical guide to obtain standardized results of the specific fields; wherein the specific field is symptom information of infectious disease;
and obtaining a medical knowledge screening library corresponding to the infectious diseases according to the standardized result of the specific field.
In an exemplary embodiment of the present disclosure, the infectious disease-based medical data screening apparatus further includes:
the statistic module can be used for carrying out statistics on the predicted value and predicting the number of the infectious diseases according to the statistical result;
an optimization module can be configured to optimize the decision tree based on an actual infectious agent count and a predicted infectious agent count of the infectious disease.
In an exemplary embodiment of the present disclosure, optimizing the decision tree based on the actual population of infectious diseases and the predicted population of infectious diseases comprises:
constructing a loss function based on the actual infectious population of the infectious disease and the predicted infectious population, and judging whether the function value of the loss function is greater than a preset threshold value;
and when the function value of the loss function is judged to be larger than the preset threshold value, adjusting the decision tree until the function value of the loss function is not larger than the preset threshold value.
In an exemplary embodiment of the present disclosure, the infectious disease-based medical data screening apparatus further includes:
and the diagnosis and treatment scheme matching module can be used for matching a recommended diagnosis and treatment scheme corresponding to the predicted value from the clinical decision support system and sending the recommended diagnosis and treatment scheme to the user side.
The specific details of each module in the infectious disease-based medical data screening apparatus are described in detail in the corresponding infectious disease-based medical data screening method, and therefore, the detailed description thereof is omitted here.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the invention. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, although the steps of the methods of the present invention are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
In an exemplary embodiment of the present invention, there is also provided an electronic device capable of implementing the above method.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 700 according to this embodiment of the invention is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 7, electronic device 700 is embodied in the form of a general purpose computing device. The components of the electronic device 700 may include, but are not limited to: the at least one processing unit 710, the at least one memory unit 720, a bus 730 connecting different system components (including the memory unit 720 and the processing unit 710), and a display unit 740.
Wherein the storage unit stores program code that is executable by the processing unit 710 such that the processing unit 710 performs the steps according to various exemplary embodiments of the present invention as described in the above section "exemplary method" of the present specification.
For example, the processing unit 710 may perform step S110 as shown in fig. 1: receiving a plurality of data screening requests input by a user side according to screening conditions; wherein the screening condition is symptom information corresponding to the infectious disease; step S120: responding to each data screening request, and matching a decision tree corresponding to each screening request from a clinical decision support system; step S130: and searching the decision tree layer by layer, determining leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes from the decision tree, and sending the predicted values to the user side.
The storage unit 720 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)7201 and/or a cache memory unit 7202, and may further include a read only memory unit (ROM) 7203.
The storage unit 720 may also include a program/utility 7204 having a set (at least one) of program modules 7205, such program modules 7205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 700 may also communicate with one or more external devices 800 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 700, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 700 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 750. Also, the electronic device 700 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the internet) via the network adapter 760. As shown, the network adapter 760 communicates with the other modules of the electronic device 700 via the bus 730. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) execute the method according to the embodiment of the present invention.
In an exemplary embodiment of the present invention, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above section "exemplary methods" of the present description, when said program product is run on the terminal device. For example, the program code may be configured to cause the terminal device to perform step S110 as shown in fig. 1: receiving a plurality of data screening requests input by a user side according to screening conditions; wherein the screening condition is symptom information corresponding to the infectious disease; step S120: responding to each data screening request, and matching a decision tree corresponding to each screening request from a clinical decision support system; step S130: and searching the decision tree layer by layer, determining leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes from the decision tree, and sending the predicted values to the user side.
According to the program product for realizing the method, the portable compact disc read only memory (CD-ROM) can be adopted, the program code is included, and the program product can be operated on terminal equipment, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
Claims (6)
1. A method for screening medical data based on infectious diseases, comprising:
receiving a plurality of data screening requests input by a user side according to screening conditions; wherein the screening conditions comprise the existence of fever symptoms, fever duration, chronic disease history and epidemiological history;
responding to each data screening request, and matching a decision tree corresponding to each screening request from a clinical decision support system; wherein the decision tree is determined by: carrying out standardization processing on a specific field in the medical guideline through the ICD-10 to obtain a standardization result of the specific field; wherein the specific field is symptom information of infectious disease; obtaining a medical knowledge screening library corresponding to the infectious disease according to the standardized result of the specific field; wherein the medical knowledge screening library comprises the specific field and a standardized result of the specific field; extracting a root node and a child node corresponding to the root node from the medical knowledge screening library according to the sequence of the occurrence of the symptom information of the infectious disease; generating the decision tree according to the root node and the child nodes corresponding to the root node, and storing the decision tree into a clinical decision support system;
searching the decision tree layer by layer, determining leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes from the decision tree, and sending the predicted values to the user side;
counting the predicted value, and predicting the number of infectious diseases according to the counting result;
constructing a loss function based on the actual infectious population of the infectious disease and the predicted infectious population, and judging whether the function value of the loss function is greater than a preset threshold value; when the function value of the loss function is judged to be larger than the preset threshold value, the decision tree is adjusted until the function value of the loss function is not larger than the preset threshold value; wherein the loss function comprises a mean square error or a sigmoid function.
2. An infectious disease-based medical data screening method according to claim 1, further comprising:
and matching a recommended diagnosis and treatment scheme corresponding to the predicted value from the clinical decision support system, and sending the recommended diagnosis and treatment scheme to the user side.
3. An infectious disease-based medical data screening device, comprising:
the receiving module is used for receiving a plurality of data screening requests input by the user side according to the screening conditions; wherein the screening conditions comprise the existence of fever symptoms, fever duration, chronic disease history and epidemiological history;
a matching module for responding each data screening request and matching a decision tree corresponding to each screening request from a clinical decision support system; wherein the decision tree is determined by: carrying out standardization processing on a specific field in the medical guideline through the ICD-10 to obtain a standardization result of the specific field; wherein the specific field is symptom information of infectious disease; obtaining a medical knowledge screening library corresponding to the infectious disease according to the standardized result of the specific field; wherein the medical knowledge screening library comprises the specific field and a standardized result of the specific field; extracting a root node and a child node corresponding to the root node from the medical knowledge screening library according to the sequence of the occurrence of the symptom information of the infectious disease; generating the decision tree according to the root node and the child nodes corresponding to the root node, and storing the decision tree into a clinical decision support system;
the searching module is used for searching the decision tree layer by layer, determining leaf nodes corresponding to the data screening requests and predicted values corresponding to the leaf nodes from the decision tree, and sending the predicted values to the user side;
the statistic module is used for carrying out statistics on the predicted value and predicting the number of the infectious diseases according to the statistic result;
the optimization module is used for constructing a loss function based on the actual infectious population of the infectious disease and the predicted infectious population and judging whether the function value of the loss function is larger than a preset threshold value or not; when the function value of the loss function is judged to be larger than the preset threshold value, the decision tree is adjusted until the function value of the loss function is not larger than the preset threshold value; wherein the loss function comprises a mean square error or a sigmoid function.
4. An infectious disease-based medical data screening system, comprising:
the system comprises a user side, a server and a data screening request sending module, wherein the user side is used for receiving screening conditions input by a user, generating a data screening request according to the screening conditions and sending the data screening request to the server;
a server connected to the user terminal network for implementing the infectious disease-based medical data screening method according to any one of claims 1-2;
and the clinical decision support system is arranged in the server and used for storing the decision tree.
5. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method for infectious disease-based medical data screening according to any one of claims 1-2.
6. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the infectious disease-based medical data screening method of any of claims 1-2 via execution of the executable instructions.
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