CN117238425A

CN117238425A - Method and device for generating inquiry medical records, electronic equipment and storage medium

Info

Publication number: CN117238425A
Application number: CN202311072252.0A
Authority: CN
Inventors: 于生元; 董钊; 韩珣; 黄思阳; 尹梓名; 谢锋波
Original assignee: Shanghai Aimu Medical Technology Co ltd; First Medical Center of PLA General Hospital
Current assignee: Shanghai Aimu Medical Technology Co ltd; First Medical Center of PLA General Hospital
Priority date: 2023-08-24
Filing date: 2023-08-24
Publication date: 2023-12-15

Abstract

The disclosure provides a method, a device, electronic equipment and a storage medium for generating a query medical record. One embodiment of the method comprises the following steps: by presenting the pre-consultation keyword display object and the game interaction mode that the target user can execute keyword classification operation on the pre-consultation keyword display object, the target user can classify the pre-consultation keyword in a limited time through different keyword classification operations without filling complete data, so that multidimensional data filling in a consultation medical record is completed rapidly, the efficiency of collecting information of the consultation medical record is improved, and convenience, comfort and coordination of an online consultation process of the user can be improved.

Description

Method and device for generating inquiry medical records, electronic equipment and storage medium

Technical Field

The embodiment of the disclosure relates to the technical field of internet medical treatment, in particular to a method, a device, electronic equipment and a storage medium for generating a consultation medical record.

Background

In the background of the increasing popularity of the mobile internet, more and more people select an online platform to perform online inquiry and the like. The large multi-line up-consultation process typically requires the patient to fill in a large amount of information, which is time consuming and may also affect the accuracy of the diagnostic results due to incomplete information filling.

Therefore, it is desirable to provide a disease interrogation solution that is convenient for the user to operate, saves time for the user, and accurately describes the condition.

Disclosure of Invention

The embodiment of the disclosure provides a method, a device, electronic equipment and a storage medium for generating a consultation medical record.

In a first aspect, embodiments of the present disclosure provide a method for generating a medical record for inquiry, the method comprising:

the following pre-interrogation operations are performed: presenting a current pre-consultation keyword display object associated with a current pre-consultation keyword, wherein the current pre-consultation keyword belongs to a pre-consultation keyword set; responding to the detection of a keyword classification operation of a target user on the current pre-consultation keyword display object, determining a classification result of the current pre-consultation keyword according to the keyword classification operation, and storing the current pre-consultation keyword and the corresponding classification result into a pre-consultation keyword classification result sequence corresponding to the target user; determining whether a pre-consultation ending condition is met based on the pre-consultation keyword classification result sequence; ending the pre-consultation operation in response to determining satisfaction; in response to determining that the preset inquiry keyword is not met, determining a preset inquiry keyword to be presented in the preset inquiry keyword set based on the preset inquiry keyword classification result sequence, determining the determined preset inquiry keyword as the current preset inquiry keyword, and continuing to execute the preset inquiry operation;

And generating the inquiry medical records of the target user according to the pre-inquiry keyword classification result sequence.

In some optional embodiments, the generating the medical records of the target user according to the classification result sequence of the pre-consultation keywords includes:

determining whether the classification result sequence of the pre-consultation keywords meets the consultation ending condition according to a pre-constructed consultation information knowledge graph;

responding to the determination of satisfaction, and generating a query medical record of the target user according to the query information knowledge graph and the pre-query keyword classification result sequence;

in response to determining that the query information is not satisfied, determining to-be-queried information for the target user according to the query information knowledge graph and the pre-query keyword classification result sequence;

generating and presenting questions to be queried according to the information to be queried, and acquiring answer contents of the target user aiming at the questions to be queried;

and generating a query medical record of the target user according to the answer content of the target user for the question to be queried and the pre-query keyword classification result sequence.

In some alternative embodiments, prior to performing the pre-interrogation operation, the method further comprises:

Extracting a pre-consultation keyword set based on a pre-constructed consultation information knowledge graph, wherein the consultation information knowledge graph comprises a node set and a connecting line set between nodes, the node set comprises at least two keyword nodes associated with the consultation keywords and corresponding attribute information, and the consultation keywords comprise the pre-consultation keywords;

according to the connecting lines between any two keyword nodes and the attribute information of the query keywords corresponding to each keyword node, determining the weight information of each pre-query keyword in the pre-query keyword set, wherein the weight information comprises a weight value.

In some optional embodiments, the presenting the current pre-query keyword display object associated with the current pre-query keyword includes:

determining the pre-consultation keywords with the weight values larger than or equal to a preset weight threshold value in the pre-consultation keyword set as current pre-consultation keywords;

and carrying out visualization processing on the current pre-consultation keywords, and generating and presenting a current pre-consultation keyword display object associated with the current pre-consultation keywords.

In some optional embodiments, the determining, based on the classification result sequence of the pre-query keyword, a pre-query keyword to be presented in the pre-query keyword set, determining the determined pre-query keyword as the current pre-query keyword, and continuing to perform the pre-query operation, including:

Updating the weight value of the pre-consultation keywords in the pre-consultation keyword set based on the pre-consultation keyword classification result sequence and the keyword nodes corresponding to each pre-consultation keyword in the pre-consultation keyword set in the consultation information knowledge graph;

determining the pre-consultation keywords with the updated weight values larger than or equal to the preset weight threshold value in the pre-consultation keyword set as pre-consultation keywords to be presented;

and determining the determined pre-consultation keywords as the current pre-consultation keywords, and continuing to execute the pre-consultation operation.

In some optional embodiments, the responding to the detection of the keyword classification operation of the target user for the current pre-query keyword display object, determining the classification result of the current pre-query keyword according to the keyword classification operation, and storing the current pre-query keyword and the corresponding classification result into the classification result sequence corresponding to the target user includes:

in response to detecting a first keyword classification operation of the target user on the current pre-consultation keyword display object, determining that a classification result of the current pre-consultation keyword is a positive classification result, and correspondingly storing the current pre-consultation keyword and the positive classification result into a pre-consultation keyword classification result sequence corresponding to the target user; and/or

And responding to the detection of a second keyword classification operation of the target user on the current pre-consultation keyword display object, determining that the classification result of the current pre-consultation keyword is a negative classification result, and correspondingly storing the current pre-consultation keyword and the negative classification result into a pre-consultation keyword classification result sequence corresponding to the target user.

In some alternative embodiments, the pre-interrogation operation further comprises:

and stopping presenting the pre-consultation keyword display object in response to the fact that the time for presenting the current pre-consultation keyword display object is greater than or equal to a preset presentation duration threshold and keyword classification operation aiming at the current pre-consultation keyword display object is not detected, determining that the classification result of the current pre-consultation keyword is an unknown classification result, and correspondingly storing the current pre-consultation keyword and the unknown classification result into the pre-consultation keyword classification result sequence.

In a second aspect, embodiments of the present disclosure provide a medical record generating apparatus for inquiry, the apparatus including:

a pre-interrogation unit configured to perform the following pre-interrogation operations: presenting a current pre-consultation keyword display object associated with a current pre-consultation keyword, wherein the current pre-consultation keyword belongs to a pre-consultation keyword set; responding to the detection of a keyword classification operation of a target user on the current pre-consultation keyword display object, determining a classification result of the current pre-consultation keyword according to the keyword classification operation, and storing the current pre-consultation keyword and the corresponding classification result into a pre-consultation keyword classification result sequence corresponding to the target user; determining whether a pre-consultation ending condition is met based on the pre-consultation keyword classification result sequence; ending the pre-consultation operation in response to determining satisfaction; in response to determining that the preset inquiry keyword is not met, determining a preset inquiry keyword to be presented in the preset inquiry keyword set based on the preset inquiry keyword classification result sequence, determining the determined preset inquiry keyword as the current preset inquiry keyword, and continuing to execute the preset inquiry operation;

And the medical record generating unit is configured to generate the inquiry medical record of the target user according to the pre-inquiry keyword classification result sequence.

In some optional embodiments, the medical record generation unit is further configured to:

In some alternative embodiments, the apparatus further comprises: a keyword and weight determination unit configured to, prior to performing the pre-inquiry operation:

In a third aspect, embodiments of the present disclosure provide an electronic device, comprising: one or more processors; and a storage device having one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement the method as described in any of the implementations of the first aspect.

In a fourth aspect, embodiments of the present disclosure provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by one or more processors, implements a method as described in any of the implementations of the first aspect.

In order to reduce the complexity and information input time of inputting disease description information by a user in the existing online inquiry process, the inquiry medical record generation method, device, electronic equipment and storage medium provided by the embodiment of the disclosure generate inquiry medical records on the basis of a pre-inquiry keyword classification result sequence obtained after pre-inquiry through executing pre-inquiry operation. Wherein the pre-interrogation operation includes: first, a current pre-consultation keyword display object associated with a current pre-consultation keyword is presented. And then, responding to the keyword classification operation of the target user aiming at the current pre-consultation keyword display object, determining the classification result of the current pre-consultation keyword according to the keyword classification operation, and storing the current pre-consultation keyword and the corresponding classification result into a pre-consultation keyword classification result sequence corresponding to the target user. Then, based on the pre-consultation keyword classification result sequence, whether the pre-consultation ending condition is satisfied is determined. If it is determined that the pre-consultation end condition is satisfied, the pre-consultation operation is ended. If the pre-consultation ending condition is not met, determining pre-consultation keywords to be presented in a pre-consultation keyword set based on the pre-consultation keyword classification result sequence, determining the determined pre-consultation keywords as current pre-consultation keywords, and continuing to execute the pre-consultation operation. The method comprises the steps that a target user can conduct game interaction of keyword classification operation on a pre-consultation keyword display object by means of presenting the pre-consultation keyword display object and the target user can conduct different keyword classification operation within a limited time, classification of the pre-consultation keyword is achieved, complete data are not required to be filled by the user, multidimensional data filling in a consultation medical record is achieved rapidly, efficiency of information collection of the consultation medical record is improved, and convenience, comfort and matching degree of an online consultation process of the user can be improved.

Drawings

Other features, objects and advantages of the present disclosure will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention. In the drawings:

FIG. 1 is an exemplary system architecture diagram in which an embodiment of the present disclosure may be applied;

FIG. 2A is a flow chart of one embodiment of a method of generating a medical query according to the present disclosure;

FIG. 2B is an exploded flow chart of one embodiment of step 201 according to the present disclosure;

FIG. 2C is an exploded flow chart of one embodiment of step 2012 according to the present disclosure;

FIG. 2D is an exploded flow chart according to one embodiment of step 202 of the present disclosure;

FIG. 2E is an exploded flow chart of one embodiment of step 2011 according to the present disclosure;

FIG. 2F is an exploded flow chart of one embodiment of step 2013 according to the present disclosure;

FIG. 3 is a schematic structural view of one embodiment of a questioning medical record generation device according to the present disclosure;

fig. 4 is a schematic diagram of a computer system suitable for use in implementing embodiments of the present disclosure.

Detailed Description

The present disclosure is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.

It should be noted that, without conflict, the embodiments of the present disclosure and features of the embodiments may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

FIG. 1 illustrates an exemplary system architecture 100 in which embodiments of the present disclosure of a method, apparatus, electronic device, and storage medium for generating a medical query can be applied.

As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as an online inquiry class application, a natural language processing class application, a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, and the like, may be installed on the terminal devices 101, 102, 103.

The terminal devices 101, 102, 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices having an information input device (e.g., keyboard, mouse, touch screen, etc.) and a display device (e.g., display screen or touch screen), including but not limited to smart phones, tablet computers, electronic book readers, MP3 players (Moving Picture Experts Group Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving Picture Experts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the above-listed terminal apparatuses. Which may be implemented as multiple software or software modules (e.g., to provide a medical record generation service), or as a single software or software module. The present invention is not particularly limited herein.

In some cases, the method for generating a medical record for inquiry provided by the present disclosure may be performed by the terminal device 101, 102, 103, and accordingly, the apparatus for generating a medical record for inquiry may be provided in the terminal device 101, 102, 103. In this case, the system architecture 100 may not include the server 105.

In some cases, the method for generating a medical record for a interview provided in the present disclosure may be performed by the terminal device 101, 102, 103 and the server 105 together, for example, the step of "performing a pre-interview operation" may be performed by the terminal device 101, 102, 103, the step of "generating a medical record for a target user according to a pre-interview keyword classification result sequence" may be performed by the server 105, and so on. The present disclosure is not limited in this regard. Accordingly, the inquiry medical record generating device may also be respectively provided in the terminal devices 101, 102, 103 and the server 105.

In some cases, the method for generating a medical record for inquiry provided by the present disclosure may be executed by the server 105, and accordingly, the apparatus for generating a medical record for inquiry may also be disposed in the server 105, where the system architecture 100 may not include the terminal devices 101, 102, 103.

The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster formed by a plurality of servers, or as a single server. When server 105 is software, it may be implemented as a plurality of software or software modules (e.g., to provide distributed services), or as a single software or software module. The present invention is not particularly limited herein.

It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

With continued reference to fig. 2A, a flow 200 of one embodiment of a method of generating a medical questionnaire according to the present disclosure is shown, the method comprising the steps of:

in step 201, a pre-consultation operation is performed.

In this embodiment, the execution subject of the inquiry medical record generation method (for example, the terminal device shown in fig. 1) may execute the pre-inquiry operation. Here, the pre-inquiry operation includes steps 2011 to 2015 as shown in fig. 2B:

in step 2011, a current pre-consultation keyword display object associated with the current pre-consultation keyword is presented.

In this embodiment, the current pre-consultation keywords belong to a pre-consultation keyword set.

The current pre-query keyword display object may be various display objects associated with the current pre-query keyword. For example, the current pre-inquiry keyword display object may be in the form of a colored bubble, a bar brick, or the like, and the current pre-inquiry keyword may be displayed in the colored bubble or the bar brick.

The set of pre-interview keywords may be predetermined according to a particular interview scenario using various implementations. The pre-consultation keywords are used for characterizing a certain consultation question or are used for characterizing a certain consultation question and corresponding answer content. It is understood that the inquiry question may be a question related to a symptom of the disease. The pre-consultation keywords may generally represent relevant attributes of a disease that may be used for diagnosis. For example, the relevant attributes may include, but are not limited to: features, regularity, pain level, frequency, specific disease characteristics, etc.

As an example, assume that the current questioning scenario is headache specialty. The preset inquiry keywords may be a set of keywords related to various degrees, symptoms, frequencies, etc. related to headache.

In step 2012, in response to detecting the keyword classification operation of the target user on the current pre-consultation keyword display object, determining a classification result of the current pre-consultation keyword according to the keyword classification operation, and storing the current pre-consultation keyword and the corresponding classification result into a pre-consultation keyword classification result sequence corresponding to the target user.

In this embodiment, after the execution body presents the current pre-query keyword display object, the target user may select to execute different keyword classification operations on the current pre-query keyword display object according to the actual situation of the target user. Then, the executing body may detect the keyword classification operation, determine a classification result of the current pre-query keyword according to the detected specific keyword classification operation type, and store the current pre-query keyword and the corresponding classification result into a pre-query keyword classification result sequence corresponding to the target user.

Here, the target user's corresponding pre-consultation keyword classification result sequence stores the pre-consultation keywords which are arranged according to time sequence and appear in the current consultation process, and the classification results of the target user on the corresponding pre-consultation keywords.

In some alternative embodiments, step 2012 may include step 20121 as shown in fig. 2C:

in step 20121, in response to detecting the first keyword classification operation of the target user on the current pre-consultation keyword display object, determining that the classification result of the current pre-consultation keyword is a positive classification result, and correspondingly storing the current pre-consultation keyword and the positive classification result into a pre-consultation keyword classification result sequence corresponding to the target user.

Here, the first keyword classification operation may be various operations preset for performing forward evaluation on the current pre-consultation keyword display object. For example, the first keyword classification operation for the current pre-query keyword display object may be clicking or dragging the current pre-query keyword display object to the region being classified. Forward rating information may be associated with the forward classification region. For example, the positive classification region may be displayed with text information for positive evaluation such as "pair", "coincidence", "yes", "pair", "yes", "satisfaction", and the like. For another example, the positively classified region may also include an image or graphic of positive evaluation. For example, a positively classified region may present, for example: images or graphics in the form of hooks, collection baskets, trophy, etc.

In some alternative embodiments, step 2012 may also include the following step 20122:

in step 20122, in response to detecting the second keyword classification operation of the target user on the current pre-query keyword display object, determining that the classification result of the current pre-query keyword is a negative classification result, and correspondingly storing the current pre-query keyword and the negative classification result into a pre-query keyword classification result sequence corresponding to the target user.

Here, the second keyword classification operation may be various operations preset for negative evaluation of the current pre-consultation keyword display object. For example, the second keyword classification operation for the current pre-query keyword display object may be clicking or dragging the current pre-query keyword display object to a negative classification area. Negative-ranking information may be associated with the negative-ranking region. For example, the negative classification region may display text information for negative evaluation such as "no", "not conforming", "not being", "wrong", "no", "not satisfying", and the like. For another example, the negative classification region may also include a negative-rated image or graphic. For example, the negative classification region may present, for example: representing images or graphics in the form of incorrect forks, waste collection baskets, etc.

In some alternative embodiments, the pre-interrogation operation may further include step 2013 as shown in fig. 2B:

and step 2013, stopping presenting the pre-consultation keyword display object, determining that the classification result of the current pre-consultation keyword is an unknown classification result, and correspondingly storing the current pre-consultation keyword and the unknown classification result into a pre-consultation keyword classification result sequence corresponding to the target user in response to the fact that the time of presenting the current pre-consultation keyword display object is greater than or equal to a preset presentation time threshold and the keyword classification operation aiming at the current pre-consultation keyword display object is not detected.

Here, if the target user does not perform the keyword classification operation within the preset presentation duration threshold time after presenting the current pre-query keyword, it is indicated that the target user may have ambiguous meaning to the current pre-query keyword, or the target user may not know whether the situation of the target user belongs to the positive classification or the negative classification of the current pre-query keyword, and the target user ignores the problem. Therefore, the classification result of the current pre-consultation keyword can be determined to be an unknown classification result, and the current pre-consultation keyword and the unknown classification result are correspondingly stored in the pre-consultation keyword classification result sequence corresponding to the target user.

Through steps 2012 and 2013, the pre-consultation keyword classification result sequence corresponding to the target user can be updated according to the specific operation (optionally including no keyword classification operation being performed within a certain time) of the target user on the presented current pre-consultation keyword display object.

Step 2014, determining whether the pre-consultation ending condition is met based on the pre-consultation keyword classification result sequence corresponding to the target user.

Here, the corresponding pre-consultation ending condition may be preset based on the specific requirement of the actual consultation scene, and then, based on the pre-consultation keyword classification result sequence corresponding to the target user, it is determined whether the pre-consultation ending condition is satisfied.

That is, whether the pre-consultation for the target user is ended is determined based on the pre-consultation keywords which are arranged according to time sequence and appear in the current consultation process of the target user and the classification result of the target user on the corresponding pre-consultation keywords. If it is determined that the pre-consultation end condition is satisfied, the pre-consultation operation may be ended, and proceeds to step 202 execution. If it is determined that the pre-consultation end condition is not met, execution may proceed to step 2015.

As an example, the pre-consultation end condition may include at least one of the following conditions:

And (3) in the condition 1, all keywords in the pre-consultation keyword set are already present in the pre-consultation keyword classification result sequence corresponding to the target user. That is, the target user performs the keyword classification operation for each pre-consultation keyword in the pre-consultation keyword set in the present consultation, and a corresponding keyword classification result is obtained.

And 2, the proportion of the pre-consultation keywords in the pre-consultation keyword set, which appear in the pre-consultation keyword classification result sequence corresponding to the target user, is larger than a preset proportion threshold value. That is, the target user performs the keyword classification operation on at least the preset proportion threshold value of the pre-consultation keywords in the pre-consultation keyword set in the current consultation, and a corresponding keyword classification result is obtained.

And 3, judging that the corresponding classification result of each of the necessary pre-inquiry keywords in the necessary pre-inquiry keyword subset in the pre-inquiry keyword set in the pre-inquiry keyword classification result sequence corresponding to the target user is not an unknown classification result. That is, the pre-query keyword set has a subset of the must-answer pre-query keyword subset. If the target user performs the keyword classification operation on each of the necessary pre-consultation keywords in the sub-set of necessary pre-consultation keywords in the present consultation, a corresponding keyword classification result is obtained.

Step 2015, determining a pre-consultation keyword to be presented in the pre-consultation keyword set based on the pre-consultation keyword classification result sequence corresponding to the target user, and determining the determined pre-consultation keyword as a current pre-consultation keyword.

That is, if it is determined in step 2014 that the pre-consultation end condition is not satisfied, it is indicated that the pre-consultation operation is still required to be continued for the target user, but before the pre-consultation operation is continued, it is also required to determine a pre-consultation keyword to be presented in the pre-consultation keyword set based on the pre-consultation keyword classification result sequence corresponding to the target user, and determine the determined pre-consultation keyword as the current pre-consultation keyword. Then, the pre-consultation operation is continued, and the process goes to step 2011 to continue. Further, the current pre-query keyword displayed object presented in step 2011 is the current pre-query keyword determined in step 2015.

As an example, the pre-query keywords that do not appear in the pre-query keyword classification result sequence corresponding to the target user in the pre-query keyword set may be first generated into a sub-set of pre-query keywords that do not appear. Then, the pre-consultation keywords are randomly selected from the non-occurrence pre-consultation keyword set as pre-consultation keywords to be presented.

As yet another example, an unclassified pre-query keyword subset may be generated first by using pre-query keywords whose corresponding classification results are unknown classification results in the pre-query keyword classification result sequence corresponding to the target user. Then, the pre-consultation keywords are randomly selected from the unclassified pre-consultation keyword subset as pre-consultation keywords to be presented.

As yet another example, an unclassified pre-query keyword subset may also be generated first with pre-query keywords in the pre-query keyword classification result sequence corresponding to the target user, where the corresponding classification result is an unknown classification result. And then, generating a subset of the pre-consultation keywords which do not appear in the pre-consultation keyword classification result sequence corresponding to the target user from the pre-consultation keyword set. Finally, randomly selecting the pre-consultation keywords from the unclassified pre-consultation keyword subset and the unclassified pre-consultation keyword subset as the pre-consultation keywords to be presented.

Through the above step 201, the classification result of the target user for different pre-consultation keywords can be obtained, and the pre-consultation ending condition is satisfied.

Step 202, generating a query medical record of the target user according to the pre-query keyword classification result sequence.

In this embodiment, the execution body may use various implementation manners to generate the medical records of the target user according to the classification result sequence of the pre-consultation keywords corresponding to the target user.

As an example, each pre-consultation keyword may be pre-associated with a respective consultation medical record statement. And then, the executing body can splice the inquiry medical record sentences related to the pre-inquiry keywords in the pre-inquiry keyword classification result according to the appearance sequence of the pre-inquiry keyword classification result in the pre-inquiry keyword classification result sequence, so as to obtain the inquiry medical record of the target user.

For example, in a headache specialty outpatient setting, the pre-consultation keyword "very painful" may be associated with a consultation medical record statement "patient complaint very painful. The keyword of the pre-consultation is 'within one week' can be associated with the medical record sentence of the consultation 'that headache symptoms occur within one week'. "more than ten times of pre-consultation keywords" can be associated with a consultation medical record sentence "more than ten times of headache per day" and so on.

In some alternative embodiments, step 202 may include steps 2021 to 2025 as shown in fig. 2D:

step 2021, determining whether the classification result sequence of the pre-consultation keywords meets the preset consultation ending condition according to the pre-constructed knowledge graph of the consultation information.

Here, the query information knowledge graph may include a node set and a node-node connection line set, where the node set may include at least two keyword nodes associated with query keywords and corresponding attribute information. Here, the query keywords in the query information knowledge graph may include each of the pre-query keywords in the set of pre-query keywords.

In some alternative embodiments, the knowledge graph of the inquiry information may be pre-constructed by the following graph construction steps:

first, a keyword is extracted. Specifically, a technician with medical expertise can analyze the question information to be collected in a specific question scene, for example, identify related entities such as diseases, symptoms, treatment methods and the like, and extract keywords from the related entities to obtain an entity keyword set. And generating entity nodes by using different entities, wherein part of the entity nodes are associated with entity keywords.

Then, attribute extraction is performed. Specifically, the attribute corresponding to the entity keyword, such as severity of symptoms, incidence of diseases, and the like, may be extracted from a medical literature database, and the like, so as to determine the attribute value of each entity keyword corresponding to different attributes, that is, the attribute value corresponding to different attributes of the entity node is determined.

Then, relation extraction is performed. Specifically, the association relationship between the different entity nodes in the inquiry information knowledge graph is established by analyzing the obtained association relationship between different entities, such as the relationship between symptoms and symptoms, the influence of a treatment method on the symptoms and the like, namely, the association relationship between the different entity nodes is established by constructing the connection lines between the nodes in the inquiry information knowledge graph.

The connection lines between nodes can be divided into different categories for representing the relationships of the different categories. For example, inter-node connection lines may be used to represent correspondence between symptoms and diseases, and accordingly, the inter-node connection lines may connect symptom entity nodes and disease entity nodes, respectively.

Optionally, the nodes may also have an association weight, which is used to characterize the association strength between two entity nodes.

And finally, integrating the knowledge graph. The identified entity nodes, attribute information and relations are organized into a unified knowledge graph of inquiry information, so that subsequent analysis and inquiry are facilitated. Wherein, the entity node may correspond to an entity keyword. And the attribute information includes attribute values of different attributes attached to the entity node.

In some optional embodiments, the query information knowledge graph may include a pre-query keyword node associated with a pre-query keyword, where the pre-query keyword node may be associated with a weight attribute. The weight attribute of the pre-consultation keyword node is used for representing the importance degree of the pre-consultation keyword in the consultation process, and the higher the weight of the pre-consultation keyword node is, the higher the probability that the corresponding associated pre-consultation keyword appears.

Here, the condition of ending the inquiry may be preset according to a specific inquiry scenario and a specific situation of a knowledge graph of corresponding inquiry information. And then, determining whether the classification result sequence of the pre-consultation keywords meets the preset consultation ending condition according to the pre-constructed consultation information knowledge graph.

If it is determined that the preset inquiry ending condition is satisfied, which indicates that the inquiry medical record can be primarily generated for the target user according to the existing pre-inquiry keyword classification result sequence, the inquiry can be ended, that is, the inquiry is not required to be continued for the target user, and then the step 2022 is executed.

If it is determined that the preset query ending condition is not satisfied, which indicates that the query medical record cannot be generated for the target user according to the existing pre-query keyword classification result sequence, the query is not ended yet, that is, the target user needs to be continuously queried, then the step 2023 is executed.

As an example, in step 2021, according to the pre-constructed knowledge graph of the inquiry information, determining whether the classification result sequence of the pre-inquiry keyword meets the preset inquiry ending condition may be performed as follows:

firstly, each pre-inquiry keyword classification result in the pre-inquiry keyword classification result sequence is corresponding to an inquiry information knowledge graph, and the attribute value of the associated attribute of the corresponding entity node in the inquiry information knowledge graph is updated according to the pre-inquiry keyword classification result. It should be noted that, each pre-consultation keyword may be associated with an entity node in the consultation information knowledge graph or a certain attribute corresponding to the entity node.

And then, determining whether a preset inquiry ending condition is met according to the updated inquiry information knowledge graph.

For example, the preset inquiry ending condition may be that attribute values of the answer attributes associated with the preset answer entity nodes in the updated inquiry information knowledge graph are all assigned. If the preset key words are not satisfied, the target user ignores the display object corresponding to the preset inquiry key words associated with the preset necessary entity node during the execution of the preset inquiry operation, and does not perform the corresponding key word classification operation. Or, it may be that a certain preset necessary entity node is not suitable for being converted into a keyword, so that no keyword in the preset inquiry keyword set is associated with the preset necessary entity node, and further, the follow-up inquiry needs to be continued for the target user.

Step 2022, generating a query medical record of the target user according to the query information knowledge graph and the pre-query keyword classification result sequence.

If it is determined in step 2021 that the preset inquiry ending condition is satisfied, it indicates that the inquiry for the target user can be ended, so that an inquiry medical record of the target user can be generated according to the inquiry information knowledge graph and the classification result sequence of the pre-inquiry keywords.

And step 2023, determining the information to be queried for the target user according to the knowledge graph of the query information and the classification result sequence of the pre-query keywords.

Here, if it is determined in step 2021 that the preset inquiry end condition is not satisfied, it is indicated that the inquiry medical record cannot be generated for the target user according to the existing pre-inquiry keyword classification result sequence, and the inquiry needs to be continued for the target user, so that the information to be inquired for the target user may be determined according to the inquiry information knowledge graph and the pre-inquiry keyword classification result sequence.

As an example, step 2023 may be performed as follows:

firstly, each pre-inquiry keyword classification result in the pre-inquiry keyword classification result sequence is corresponding to an inquiry information knowledge graph, and the attribute value of the associated attribute of the corresponding entity node in the inquiry information knowledge graph is updated according to the pre-inquiry keyword classification result.

And then determining the answering entity node which is not assigned in the answering attributes associated with the preset answering entity node in the updated knowledge graph of the inquiry information and the corresponding attributes.

And finally, generating the information to be queried according to the unaddressed necessary entity nodes and the corresponding attributes.

The question information may include questions to be asked. Optionally, the question information may further include candidate options corresponding to the question to be asked.

After step 2023 is performed, step 2024 may be performed.

Step 2024, generating and presenting the question to be asked according to the information to be asked, and obtaining the answer content of the target user for the question to be asked.

Alternatively, when the question information to be questioned includes candidate options, the candidate options may also be presented.

After the question to be asked is presented, the target user can answer in a targeted manner, and then the execution subject can acquire the answer content of the target user for the question to be asked.

After step 2024 is performed, step 2025 may be performed.

Step 2025, generating a query medical record of the target user according to the answer content of the target user for the question to be queried and the pre-query keyword classification result sequence.

For example, the executing body may first generate a first medical record according to a pre-consultation keyword classification result sequence corresponding to the target user. Then, a second medical record can be generated according to the answer content of the target user for the question to be diagnosed. And finally, merging the first inquiry medical record and the second inquiry medical record to obtain the inquiry medical record of the target user.

In some alternative embodiments, the execution body may perform step 201 'and step 202' shown in fig. 2A before performing step 201:

step 201', extracting a pre-consultation keyword set based on a pre-constructed consultation information knowledge graph.

Here, the inquiry information knowledge graph may include a node set and an inter-node connection line set. The node set may include at least two keyword nodes associated with a query keyword and corresponding attribute information. And, the inquiry keywords include pre-inquiry keywords.

Step 202', determining weight information of each pre-consultation keyword in the pre-consultation keyword set according to the connecting line between any two keyword nodes and the attribute information of the corresponding consultation keyword of each keyword node.

The weight information may include a weight value.

Based on the optional embodiments of step 201 'and step 202' described above, optionally, step 2011, presenting the current pre-query keyword display object associated with the current pre-query keyword may include step 20111 and step 20112 as shown in fig. 2E:

in step 20111, the pre-consultation keywords with the weight value greater than or equal to the preset weight threshold in the pre-consultation keyword set are determined to be current pre-consultation keywords.

In step 20112, the current pre-consultation keywords are visualized, and a current pre-consultation keyword display object associated with the current pre-consultation keywords is generated and presented.

Based on the optional embodiments of step 201 'and step 202' above, optionally, step 2013, determining a pre-query keyword to be presented in the pre-query keyword set based on the pre-query keyword classification result sequence corresponding to the target user, determining the determined pre-query keyword as the current pre-query keyword, and continuing to perform the pre-query operation, which may include steps 20131 to 20133 shown in fig. 2F:

step 20131, updating the weight value of the pre-consultation keywords in the pre-consultation keyword set based on the pre-consultation keyword classification result sequence corresponding to the target user and the keyword nodes corresponding to each pre-consultation keyword in the pre-consultation keyword set in the consultation information knowledge graph.

And step 20132, determining the pre-consultation keywords with the updated weight values being greater than or equal to a preset weight threshold in the pre-consultation keyword set as pre-consultation keywords to be presented.

And step 20133, determining the determined pre-consultation keywords as current pre-consultation keywords, and continuing to execute the pre-consultation operation.

According to the method for generating the medical record of the inquiry provided by the embodiment of the disclosure, the medical record of the inquiry is generated on the basis of the classification result sequence of the keywords of the pre-inquiry obtained after the pre-inquiry through executing the pre-inquiry operation. Wherein the pre-interrogation operation includes: first, a current pre-consultation keyword display object associated with a current pre-consultation keyword is presented. And then, responding to the keyword classification operation of the target user aiming at the current pre-consultation keyword display object, determining the classification result of the current pre-consultation keyword according to the keyword classification operation, and storing the current pre-consultation keyword and the corresponding classification result into a pre-consultation keyword classification result sequence corresponding to the target user. Then, based on the pre-consultation keyword classification result sequence, whether the pre-consultation ending condition is satisfied is determined. If it is determined that the pre-consultation end condition is satisfied, the pre-consultation operation is ended. If the pre-consultation ending condition is not met, determining pre-consultation keywords to be presented in a pre-consultation keyword set based on the pre-consultation keyword classification result sequence, determining the determined pre-consultation keywords as current pre-consultation keywords, and continuing to execute the pre-consultation operation. The method comprises the steps that a target user can conduct game interaction of keyword classification operation on a pre-consultation keyword display object by means of presenting the pre-consultation keyword display object and the target user can conduct different keyword classification operation within a limited time, classification of the pre-consultation keyword is achieved, complete data are not required to be filled by the user, multidimensional data filling in a consultation medical record is achieved rapidly, efficiency of information collection of the consultation medical record is improved, and convenience, comfort and matching degree of an online consultation process of the user can be improved.

With further reference to fig. 3, as an implementation of the method shown in the foregoing figures, the present disclosure provides an embodiment of a query medical record generating apparatus, where an embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 2A, and the apparatus may be specifically applied to various electronic devices.

As shown in fig. 3, the inquiry medical record generating apparatus 300 of the present embodiment includes: a pre-consultation unit 301 and a medical record generation unit 302. Wherein the pre-interrogation unit 301 is configured to perform the following pre-interrogation operations: presenting a current pre-consultation keyword display object associated with a current pre-consultation keyword, wherein the current pre-consultation keyword belongs to a pre-consultation keyword set; responding to the detection of a keyword classification operation of a target user on the current pre-consultation keyword display object, determining a classification result of the current pre-consultation keyword according to the keyword classification operation, and storing the current pre-consultation keyword and the corresponding classification result into a pre-consultation keyword classification result sequence corresponding to the target user; determining whether a pre-consultation ending condition is met based on the pre-consultation keyword classification result sequence; ending the pre-consultation operation in response to determining satisfaction; in response to determining that the preset inquiry keyword is not met, determining a preset inquiry keyword to be presented in the preset inquiry keyword set based on the preset inquiry keyword classification result sequence, determining the determined preset inquiry keyword as the current preset inquiry keyword, and continuing to execute the preset inquiry operation; the medical record generating unit 302 is configured to generate a medical record of the target user according to the classification result sequence of the pre-consultation keywords.

In this embodiment, the specific processing of the pre-query unit 301 and the medical record generating unit 302 of the query medical record generating device 300 and the technical effects thereof may refer to the related descriptions of the step 201 and the step 202 in the corresponding embodiment of fig. 2A, and are not described herein.

In some alternative embodiments, the medical record generation unit 302 can be further configured to:

In some alternative embodiments, the apparatus 300 may further include: the keyword and weight determination unit 303 is configured to, prior to performing the pre-inquiry operation:

In some optional embodiments, the presenting the current pre-query keyword display object associated with the current pre-query keyword may include:

In some optional embodiments, the determining, based on the classification result sequence of the pre-query keyword, a pre-query keyword to be presented in the pre-query keyword set, determining the determined pre-query keyword as the current pre-query keyword, and continuing to perform the pre-query operation may include:

In some optional embodiments, the responding to the detection of the keyword classification operation of the target user for the current pre-query keyword display object, determining a classification result of the current pre-query keyword according to the keyword classification operation, and storing the current pre-query keyword and the corresponding classification result into a classification result sequence corresponding to the target user may include:

In some alternative embodiments, the pre-interrogation operation may further comprise:

It should be noted that, the implementation details and technical effects of each unit in the medical record generating device for inquiry provided in the embodiments of the present disclosure may refer to the descriptions of other embodiments in the present disclosure, which are not described herein again.

Referring now to FIG. 4, there is illustrated a schematic diagram of a computer system 400 suitable for use in implementing the electronic device of the present disclosure. The computer system 400 depicted in fig. 4 is merely an example, and should not be taken as limiting the functionality and scope of use of embodiments of the present disclosure.

As shown in fig. 4, the computer system 400 may include a processing device (e.g., central processing unit, graphics processor, etc.) 401 that may perform various suitable actions and processes in accordance with programs stored in a Read Only Memory (ROM) 402 or loaded from a storage device 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the computer system 400 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.

In general, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, etc.; an output device 407 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 408 including, for example, magnetic tape, hard disk, etc.; and a communication device 409. The communications apparatus 409 may allow the computer system 400 to communicate with other devices wirelessly or by wire to exchange data. While fig. 4 illustrates a computer system 400 having electronic devices with various means, it should be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.

In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via communications device 409, or from storage 408, or from ROM 402. The above-described functions defined in the methods of the embodiments of the present disclosure are performed when the computer program is executed by the processing device 401.

It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, 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. In the context of this disclosure, a computer-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. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer 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 computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.

The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to implement a method of generating a medical query record as shown in the embodiment and optional implementation of fig. 2A.

Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ 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 computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units involved in the embodiments described in the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The name of the unit does not limit the unit itself in some cases, for example, the medical record generating unit may also be described as "a unit that generates a medical record of a target user according to a classification result sequence of the pre-query keyword".

The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by persons skilled in the art that the scope of the disclosure referred to in this disclosure is not limited to the specific combinations of features described above, but also covers other embodiments which may be formed by any combination of features described above or equivalents thereof without departing from the spirit of the disclosure. Such as those described above, are mutually substituted with the technical features having similar functions disclosed in the present disclosure (but not limited thereto).

Claims

1. A method for generating a medical record of a consultation, comprising:

2. The method of claim 1, wherein generating the medical query of the target user based on the sequence of pre-query keyword classification results comprises:

3. The method of claim 1, wherein prior to performing the pre-interrogation operation, the method further comprises:

4. The method of claim 3, wherein presenting the current pre-consultation keyword display object associated with the current pre-consultation keyword comprises:

5. The method of claim 3, wherein the determining a pre-query keyword to be presented in the set of pre-query keywords based on the sequence of pre-query keyword classification results, determining the determined pre-query keyword as the current pre-query keyword, and continuing to perform the pre-query operation comprises:

determining the pre-consultation keywords with the updated weight values larger than or equal to a preset weight threshold value in the pre-consultation keyword set as pre-consultation keywords to be presented;

6. The method according to claim 1, wherein the responding to the detection of the keyword classification operation of the target user for the current pre-consultation keyword display object, determining the classification result of the current pre-consultation keyword according to the keyword classification operation, and storing the current pre-consultation keyword and the corresponding classification result into the classification result sequence corresponding to the target user comprises:

7. The method of claim 1, wherein the pre-interrogation operation further comprises:

8. A medical record generating device for inquiry, comprising:

9. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon,

the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-7.

10. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by one or more processors implements the method of any of claims 1-7.