CN109036544B - Medical information pushing method, medical information pushing device, computer equipment and storage medium - Google Patents
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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
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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Abstract
The application relates to a medical information pushing method, a medical information pushing device, computer equipment and a storage medium. The method comprises the following steps: receiving a service request message; when the service request type of the service request message is registration inquiry, inquiring an inquiry dialogue template corresponding to the service request message; responding to the service request message through a consultation dialogue template to conduct dialogue consultation; obtaining symptom information according to question-answer data in the dialogue question-call process; inputting the disease information into a corresponding disease matching model, and performing matching treatment on the disease information through the disease matching model to obtain a disease information processing result; pushing the obtained disease information processing result. By adopting the method, the acquisition of the disease information and the processing process of the disease information can be realized without direct participation of doctors, repeated communication between doctors and patients is avoided, the processing process of medical service requests is simplified, and the feedback efficiency of medical information in medical service is improved.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a medical information pushing method, a medical information pushing device, a computer device, and a storage medium.
Background
At present, social medical resources are short, in the traditional medical service process, a patient goes to a front desk of a hospital to reserve registration, the patient goes to a corresponding department of the hospital after registration is successful, and communicates with a doctor for multiple times, so that the doctor knows the condition of the patient, and the doctor gradually analyzes and eliminates suspected cases to give out diagnosis results, finally, the doctor issues a prescription according to the diagnosis results, and the patient purchases corresponding medicines according to the prescription of the hospital.
However, in the traditional hospital medical service process, the patient is required to roll around the hospital, the process is complicated, the response to the medical service request of the patient is slow, the time consumption is long, and the feedback efficiency of medical information is low.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a medical information pushing method, apparatus, computer device, and storage medium that can improve the feedback efficiency of medical information in medical services.
A medical information pushing method, the method comprising:
receiving a service request message;
when the service request type of the service request message is registration inquiry, inquiring an inquiry dialogue template corresponding to the service request message;
responding to the service request message through a consultation dialogue template to conduct dialogue consultation;
Obtaining symptom information according to question-answer data in the dialogue question-call process;
inputting the disease information into a corresponding disease matching model, and performing matching treatment on the disease information through the disease matching model to obtain a disease information processing result;
pushing the obtained disease information processing result.
In one embodiment, the step of querying a query dialog template corresponding to a service request message includes:
extracting a request keyword from the service request message;
performing department matching on the request keywords and department keywords of each hospital function department, and determining corresponding hospital function departments according to department matching results;
query a consultation dialogue template corresponding to a hospital functional department.
In one embodiment, the step of conducting a session inquiry in response to a service request message through an inquiry session template includes:
inquiring personal archive information of a corresponding patient in the service request message;
determining a response node in a consultation dialogue template according to the service request message and the personal file information, wherein the response node is an initial question node when the dialogue consultation is carried out through the consultation dialogue template;
the session inquiry is performed by the responding node responding to the service request message.
In one embodiment, the step of determining the response node in the inquiry dialog template from the service request message and the personal profile information includes:
extracting archive keywords from the personal archive information;
obtaining a consultation keyword group by combining the request keyword and the file keyword;
sequentially carrying out node matching on the inquiry keyword groups and all inquiry nodes in the inquiry dialogue template;
and taking the unmatched inquiry node as a response node.
In one embodiment, after the step of obtaining the condition information according to the question-answer data in the dialogue question process, the method further comprises:
comparing the condition information with the personal profile information;
when the disease information is inconsistent with the personal archive information, the personal archive information is updated according to the disease information.
In one embodiment, after the step of pushing the obtained condition information processing result, the method further includes:
extracting pathological keywords in the disease information processing result;
combining the pathological keywords with the archive keywords according to preset combination conditions to obtain a prescription keyword group;
inputting the prescription key word group into a corresponding drug matching model for feature matching;
and generating prescription recommendation according to the drug list in the matching result, and pushing the prescription recommendation.
In one embodiment, the method further comprises:
when the service request type of the service request message is information subscription, inquiring a corresponding subscription information database according to the service request message;
acquiring corresponding medical subscription information from the subscription information database, and pushing the medical subscription information.
A medical information pushing device, the device comprising:
a message receiving module for receiving a service request message;
the dialogue template inquiry module is used for inquiring a consultation dialogue template corresponding to the service request message when the service request type of the service request message is registration consultation;
the dialogue inquiry module is used for responding to the service request message through the inquiry dialogue template and carrying out dialogue inquiry;
the disease information acquisition module is used for acquiring disease information according to question-answer data in the dialogue question-call process;
the disease information processing module is used for inputting the disease information into the corresponding disease matching model, and matching the disease information through the disease matching model to obtain a disease information processing result;
and the result pushing module is used for pushing the obtained symptom information processing result.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
Receiving a service request message;
when the service request type of the service request message is registration inquiry, inquiring an inquiry dialogue template corresponding to the service request message;
responding to the service request message through a consultation dialogue template to conduct dialogue consultation;
obtaining symptom information according to question-answer data in the dialogue question-call process;
inputting the disease information into a corresponding disease matching model, and performing matching treatment on the disease information through the disease matching model to obtain a disease information processing result;
pushing the obtained disease information processing result.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
receiving a service request message;
when the service request type of the service request message is registration inquiry, inquiring an inquiry dialogue template corresponding to the service request message;
responding to the service request message through a consultation dialogue template to conduct dialogue consultation;
obtaining symptom information according to question-answer data in the dialogue question-call process;
inputting the disease information into a corresponding disease matching model, and performing matching treatment on the disease information through the disease matching model to obtain a disease information processing result;
Pushing the obtained disease information processing result.
According to the medical information pushing method, the medical information pushing device, the medical information pushing computer equipment and the medical information pushing storage medium, when the service request message of the registration inquiry service request type is received, the conversation inquiry is conducted through the corresponding inquiry conversation template, the symptom information is obtained from the inquiry data in the conversation inquiry process, and finally the symptom information is input into the disease matching model to be processed, so that a symptom information processing result is obtained, and the symptom information processing result is pushed. The dialogue consultation is directly carried out through the consultation dialogue template, the obtained disease information is input into the corresponding disease matching model for processing, the disease information processing result is obtained and pushed, and the acquisition of the disease information and the processing process of the disease information do not need direct participation of doctors, so that repeated communication between doctors and patients is avoided, the processing process of medical service requests is simplified, and the feedback efficiency of medical information in medical service is improved.
Drawings
FIG. 1 is an application scenario diagram of a medical information push method in one embodiment;
FIG. 2 is a flow chart of a method of pushing medical information in an embodiment;
FIG. 3 is a flowchart illustrating a step of querying a query dialogue template corresponding to a service request message in one embodiment;
FIG. 4 is an application scenario diagram of a method of pushing medical information in another embodiment;
FIG. 5 is a flowchart of a method for pushing medical information in another embodiment;
FIG. 6 is a block diagram of a medical information delivery device according to one embodiment;
fig. 7 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The medical information pushing method provided by the application can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The terminal 102 sends a service request message to the server 104, when the server 104 determines that the service request type of the service request message is registration inquiry, the server 104 performs conversation inquiry with the terminal 102 through a corresponding inquiry conversation template, the server 104 obtains disorder information from inquiry data in the conversation inquiry process, and finally inputs the disorder information into a disease matching model for processing, obtains a disorder information processing result and pushes the disorder information processing result to the terminal 102. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smartphones, tablet computers, and portable wearable devices, and the server 104 may be implemented by a stand-alone server or a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 2, a medical information pushing method is provided, and the method is applied to the server 104 in fig. 1 for illustration, and includes the following steps:
s201: a service request message is received.
The service request message refers to a medical service request sent by the terminal 102 to the server 104, and reflects the type of medical service required by the terminal 102, such as registration inquiry, information subscription, and the like.
S203: and when the service request type of the service request message is registration inquiry, inquiring an inquiry dialogue template corresponding to the service request message.
The service request message may be a condition expression content of the patient to the doctor at the beginning of the medical service, and may include, but is not limited to, patient object information, disease location, condition expression, and the like. In particular implementations, the service request message may be in the form of, but is not limited to, a text message, a voice message, an audio-visual, or other multimedia message. For example, the service request message may be a voice message sent by the terminal 102, and the corresponding text content converted by voice recognition is "i have a very light sleep since three days ago, wake every morning, and have a very difficult fall asleep at night". By analyzing the content of the service request message, the type of service request required by the service request message can be determined. Registration inquiry refers to the process of diagnosing diseases by registering a patient to indicate that the patient needs to visit a doctor and establishing a connection with a corresponding doctor, and then inquiring the patient about occurrence, development, symptoms of the disease, treatment progress and the like of the disease in a dialogue mode. When the service request type of the service request message received by the server 104 is a registration inquiry, which indicates that the terminal 102 needs a registration inquiry service, a corresponding inquiry dialogue template is queried.
The inquiry dialogue template is a pre-constructed dialogue model for simulating the doctor-patient inquiry process, and can provide inquiry dialogue service for the patient through the server 104. In a specific implementation, the inquiry dialogue template comprises inquiry nodes and node circulation conditions, wherein the inquiry nodes reflect the questions of doctors in the process of acquiring the disease information, and corresponding inquiry messages can be generated through the inquiry nodes; the node circulation condition corresponds to the answer of the patient, and the flow direction of the consultation node is different according to the answer of different patients. Considering the characteristics of various diseases, different diseases can correspond to different inquiry dialogue contents, namely different diseases correspond to different inquiry dialogue templates, so that the targeted inquiry dialogue can be ensured.
S205: and responding to the service request message through a consultation dialogue template to conduct dialogue consultation.
After the inquiry dialogue template is obtained, the received service request message is responded through the inquiry dialogue template, namely, corresponding inquiry messages are generated and issued according to inquiry nodes in the inquiry dialogue template, so that dialogue inquiry is realized. In the process of acquiring the relevant information of the patient in the form of inquiry dialogue, the next question is selected in a targeted manner according to the answer of the patient to the previous question, so that the accuracy of acquiring the relevant information of the patient is ensured. Specifically, after the first query node generates and issues the first query message, the receiving terminal 102 receives a corresponding first answer message returned by the patient, and then selects a second query node after the first query node is circulated from the query dialogue template according to the first answer message, and generates and issues the second query message through the second query node, so that the operation of the query dialogue template is advanced, and the dialogue query is realized.
S207: and obtaining the disease information according to the question-answer data in the dialogue question-call process.
In the medical service process, a doctor records relevant information of a patient in the session communication inquiry process with the patient to obtain disease information of the patient, wherein the disease information can be used for subsequent diagnosis of the doctor, and particularly can include but is not limited to gender, age, physiological period condition, disease position, disease name and symptom expression of the patient. In this embodiment, in the process of performing a dialogue inquiry through an inquiry dialogue template, inquiry data is recorded, so as to obtain the disease information of the patient.
S209: and inputting the disease information into a corresponding disease matching model, and performing matching processing on the disease information through the disease matching model to obtain a disease information processing result.
The disease matching model includes a mapping relationship between various disease features and disease names, and the mapping relationship can be, but is not limited to, a disease feature word composition extracted from information such as disease names, disease numbers, disease objects, application drugs and the like of various diseases, and the corresponding diseases can be uniquely determined through the mapping relationship. The feature matching of the disease information and the disease features can be realized through the disease matching model, the input disease information can be subjected to disease matching processing, and the disease information processing result is output. Specifically, the disease matching model may be a naive bayes probability model obtained based on bayes algorithm, which may count the probability of each disease according to the input feature phrase. In addition, the disease matching model can also be based on a disease matching neural network obtained by an artificial neural network algorithm. The disease information is input into the disease matching model, and the disease matching model is used for matching the disease information to obtain a disease information processing result.
S211: pushing the obtained disease information processing result.
The result of the treatment of the disease information can be used as reference information when a doctor diagnoses or as a result of the diagnosis of the patient. Specifically, after obtaining the result of processing the disease information, the server 104 pushes the result to a doctor terminal for the doctor to refer to when diagnosing the patient; meanwhile, the disease information processing result can be pushed to the patient terminal, so that the patient can primarily know the disease condition of the patient, and then the patient can go to the hospital for treatment selectively.
In the medical information pushing method, when a service request message of a registration inquiry service request type is received, a conversation inquiry is conducted through a corresponding inquiry conversation template, disorder information is obtained from inquiry data in the conversation inquiry process, and finally the disorder information is input into a disease matching model for processing, a disorder information processing result is obtained, and the disorder information processing result is pushed. The dialogue consultation is directly carried out through the consultation dialogue template, the obtained disease information is input into the corresponding disease matching model for processing, the disease information processing result is obtained and pushed, and the acquisition of the disease information and the processing process of the disease information do not need direct participation of doctors, so that repeated communication between doctors and patients is avoided, the processing process of medical service requests is simplified, and the feedback efficiency of medical information in medical service is improved.
In one embodiment, as shown in fig. 3, the step of querying a consultation dialogue template corresponding to a service request message includes:
s301: the request key is extracted from the service request message.
The service request message received by the server 104 and provided by the patient is generally a natural language-based expression, which may include useless redundant information, where the service request message needs to be cleaned, and a core request keyword is extracted to improve the processing efficiency of the service request message. Specifically, extracting the request keyword from the service request message may be implemented based on a TextRank keyword extraction algorithm. The text rank keyword extraction algorithm is a graph-based ordering algorithm for texts, and the basic idea is that the text is divided into a plurality of constituent units (words and sentences) and a graph model is built, important components in the text are ordered by utilizing a voting mechanism, and keyword extraction and abstract can be realized by utilizing the information of a single document.
In a specific application, the judgment can be performed according to the part of speech of each phrase in the service request message, for example, pronouns, adverbs and the like can be preliminarily judged to be redundant data; the key word of the core request can be extracted by judging according to the semantics of each phrase based on the big data analysis of the clinical data. The request keywords may include, but are not limited to, the sex, age, location of the condition, symptom manifestation, and disease name of the patient. For example, a text-form service request message "headache, fever, suspected of catching a cold and fever, and severe nasal obstruction", wherein words such as "something", "suspected", "severe" are irrelevant to the disease itself, are expression forms in natural language, can be removed as redundant data, and remain request keywords closely related to the disease such as "headache", "fever", "catching a cold", "fever", "nasal obstruction", etc.
S303: and matching the request keywords with department keywords of each hospital function department, and determining the corresponding hospital function department according to the department matching result.
Generally, in the medical service process, the medical service process is subdivided into corresponding hospital functional departments, the types of diseases served by the functional departments are different, the acquisition modes of various diseases are different, namely, the contents and logic of dialogue questions and answers corresponding to various diseases are different, and the corresponding question dialogue templates are also different, so that the disease information acquisition efficiency and the effectiveness of the acquired disease information are ensured.
The hospital functional departments may be classified according to the type of diseases in medical services, for example, internal medicine (blood system diseases), surgery (external diseases), obstetrics and gynecology, and infectious departments. Specifically, after the request keywords are obtained, the request keywords are matched with department keywords of each hospital function department, and the hospital function departments corresponding to the service request messages are determined according to the matching results.
S305: query a consultation dialogue template corresponding to a hospital functional department.
After the hospital functional department corresponding to the service request message is determined, acquiring a consultation dialogue template corresponding to the hospital functional department. In this embodiment, each hospital functional department sets up the corresponding dialogue template of asking for a diagnosis respectively, when implementing in particular, can also carry out multistage division to the hospital functional department to set up the dialogue template of asking for a diagnosis respectively to multistage division department. For example, surgery may be classified secondarily into bone surgery, hepatobiliary surgery, neurosurgery, penta-otology, dermatology, urology, and burn surgery, and a consultation dialogue template may be constructed for each secondarily classified department, respectively. In a specific application, after determining the hospital functional department corresponding to the current service request message, the server 104 may acquire a corresponding inquiry dialogue template from a corresponding department server, or may acquire a corresponding inquiry dialogue template from a dialogue template server, where various inquiry dialogue templates corresponding to each hospital functional department are stored.
In this embodiment, by further determining the hospital functional department corresponding to the service request message and performing the dialogue consultation according to the consultation dialogue template corresponding to the hospital functional department, pertinence in the consultation dialogue and the advancing efficiency of the consultation dialogue are effectively improved.
In one embodiment, the step of conducting a session inquiry in response to the service request message through an inquiry session template includes: inquiring personal archive information of a corresponding patient in the service request message; determining a response node in a consultation dialogue template according to the service request message and the personal file information, wherein the response node is an initial question node when the dialogue consultation is carried out through the consultation dialogue template; the session inquiry is performed by the responding node responding to the service request message.
The service request message includes information related to the patient object, and the personal archive information of the corresponding patient is queried according to the service request message. The personal profile information is personal information of the patient stored in the profile database, and may include, but not limited to, gender, age, region, physical characteristics, allergic sources, past medical history, etc. The personal archive information of the patient can be used for quickly knowing the information of the patient so as to avoid the problem of repeated inquiry when the dialogue inquiry is carried out through the inquiry dialogue template. Specifically, the registration information can be directly obtained from patient registration information and health files stored in a medical system server through the server 104, wherein the registration information can be information reserved when the patient is used for registering a medical system, and generally comprises age, gender and the like; the health file is file data established by the medical service system for registered patients, and besides personal basic information such as birth date, age and gender, the health file can also record medical health information such as past medical history and allergic sources of the user.
After personal file information of a patient is obtained, known information in a consultation dialogue template is determined by integrating the service request message and the personal file information, and an initial question node of the consultation dialogue template is determined, so that when the dialogue consultation is carried out through the consultation dialogue template, the question node in the consultation dialogue template of a known answer can be skipped in a targeted manner, and the efficiency of dialogue consultation can be effectively improved. For example, after receiving a service request message sent by a patient to trigger a consultation, inquiring that a patient has a consultation treatment record 2 days before from personal archive information of the patient, determining that the patient is a review, determining that a review related node in a consultation dialogue template is an initial question node, and performing a consultation dialogue through the initial question node.
After the response node is determined, the response node in the consultation dialogue template responds to the service request message sent by the patient, namely, a corresponding consultation message is generated and issued according to the response node, so that dialogue consultation is realized. In the process of acquiring relevant information of a patient disease through a consultation dialogue form, the next question is selected in a targeted manner according to the answer of the patient to the previous question, so that the accuracy of acquiring the disease information is ensured.
In this embodiment, by analyzing known information from the service request message and the personal archive information, the response node of the inquiry dialogue template is determined, so that the problem of repeated inquiry during the inquiry dialogue can be effectively avoided, and the propulsion efficiency of the inquiry dialogue is effectively improved.
In one embodiment, the step of determining the response node in the inquiry dialog template from the service request message and the personal profile information includes: extracting archive keywords from the personal archive information; obtaining a consultation keyword group by combining the request keyword and the file keyword; sequentially carrying out node matching on the inquiry keyword groups and all inquiry nodes in the inquiry dialogue template; and taking the unmatched inquiry node as a response node.
The service request message is based on the content of natural language expression, so that data cleaning is needed to extract keywords. In addition, considering the personal profile information including various information such as the sex, age, region, physical characteristics, allergen and past medical history of the patient, not all data in the personal profile information need to be considered for determining the response node of the inquiry dialogue template, and the profile keywords related to the determination of the response node need to be extracted therefrom. The extraction of the archive keywords from the personal archive information may also be implemented based on a TextRank keyword extraction algorithm.
After the file keywords are obtained, the file keywords and the request keywords can be combined according to preset combination conditions to obtain inquiry keyword groups. The preset combination conditions may be combinations in a fixed order such as patient sex, age, disease site, disease name, disease manifestation, etc. In addition, file keywords and complaint keywords can be combined indiscriminately and simply, so that the intermediate operation process is reduced, and the processing efficiency is improved.
After the inquiry key word group is obtained, partial disease related information is obtained, in order to avoid repeated inquiry during inquiry dialogue, node matching is carried out on the inquiry key word group and each inquiry node in the inquiry dialogue template in sequence, and unmatched inquiry nodes are used as response nodes. When the inquiry key word group is matched with the inquiry node, the inquiry node can be matched according to the sequence of the inquiry node in the inquiry dialogue template, if the inquiry is successful, the patient response data required by the inquiry content corresponding to the inquiry node is acquired, repeated inquiry is not required, and the node can be skipped. When the matching is unsuccessful, the response data needed by the inquiry node is not acquired, and the inquiry needs to be carried out, namely the inquiry node is used as a response node, and the operation of dialogue inquiry is advanced.
In the embodiment, the data processing amount is reduced by constructing the inquiry keyword group, the inquiry keyword group is matched with the inquiry nodes in the inquiry dialogue template, the response nodes are determined, and the initial inquiry nodes of the inquiry dialogue can be effectively and quickly determined, so that the pushing efficiency of medical information is improved.
In one embodiment, after the step of obtaining the condition information from the question-answer data in the session inquiry process, the method further comprises: comparing the condition information with the personal profile information; when the disease information is inconsistent with the personal archive information, the personal archive information is updated according to the disease information.
In the process of carrying out inquiry dialogue with a patient through the inquiry dialogue template, the latest personal information of the patient can be obtained, and the personal file information of the patient is correspondingly updated according to the latest personal information. Specifically, the obtained disease information is compared with personal archive information of a patient, the personal archive information is updated according to inconsistent disease information, and the personal archive information is updated in time, so that the validity of the information is ensured.
In one embodiment, after the step of pushing the obtained condition information processing result, the method further includes: extracting pathological keywords in the disease information processing result; combining the pathological keywords with the archive keywords according to preset combination conditions to obtain a prescription keyword group; inputting the prescription key word group into a corresponding drug matching model for feature matching; and generating prescription recommendation according to the drug list in the matching result, and pushing the prescription recommendation.
After obtaining the patient's condition information, pathological keywords such as disease location, disease name, ICD-10 disease code, symptom expression, etc. are extracted therefrom. For medical rigors, taking into consideration the medication of patients, in addition to the disease information, the individual physical characteristics of the patients need to be considered, for example, if penicillin drugs are prescribed according to the pathological keywords of the disease information only for patients with allergic sources including penicillin, the drugs may be invalid or cause serious side effects. Based on the above, after obtaining the pathological keywords, the prescription keyword group is further generated by combining the file keywords. The prescription key word group is obtained by combining pathological key words and archive key words according to preset combination conditions. For example, after the priorities are classified according to preset priority classification conditions, the priorities can reflect the importance degrees, and then the priorities are combined according to the priority levels to obtain the prescription key phrase.
After the prescription key word group is obtained, the prescription key word group is input into a corresponding drug matching model for feature matching. The drug matching model comprises mapping relations of various drug characteristics, the mapping relations can be but not limited to drug characteristic word compositions extracted from information such as drug names, drug numbers, usage objects, usage, functions, usage amounts, taboos and the like of various drugs, and corresponding drugs can be uniquely determined through the mapping relations. The characteristic matching of the prescription key word group and the medicine characteristic can be realized through the medicine matching model, and the medicine matching can be carried out according to the input prescription key word group, and the matched medicine is output. Specifically, the drug matching model may be a naive bayes probability model obtained based on bayes algorithm, which can count the probability of each drug according to the input prescription keyword group, and output the drug with the highest probability.
In specific implementation, the drug matching models corresponding to the functional departments of the hospitals may be different, and at this time, after the drug matching models corresponding to the functional departments of the hospitals are queried, the prescription key word group is input for feature matching, so as to obtain a corresponding output result.
After a matching result of the medicine matching model is obtained, generating prescription recommendation according to a medicine list in the matching result, and pushing the prescription recommendation. The prescription is a medicine list which is provided by doctors for patients, is written files of the doctors for the patients, and is the basis for the medicament personnel to allocate medicines. The prescription recommendation obtained in this embodiment may be used as a reference for a doctor to prescribe, and in particular, if the drug list in the prescription recommendation is appropriate, the prescription recommendation may be directly used as a prescription.
In one embodiment, further comprising: when the service request type of the service request message is information subscription, inquiring a corresponding subscription information database according to the service request message; acquiring corresponding medical subscription information from the subscription information database, and pushing the medical subscription information.
When the service request type of the service request message received by the server 104 is information subscription, it indicates that the service required by the terminal 102 is to acquire subscribed medical information. At this time, the subscribed medical information content, such as medical courses, health care suggestions, etc., is determined according to the service request message, and the corresponding subscription information database is queried to obtain medical subscription information and push the medical subscription information to the terminal 102. When the method is applied specifically, the server 104 may send a medical information acquisition request to the subscription server, so as to acquire corresponding medical subscription information from the subscription server and push the corresponding medical subscription information. In this embodiment, providing the medical information subscription service may provide a plurality of medical services for the terminal 102, such as fitness courses, health management plans, health food recommendations, physiotherapy guidance, and the like.
The medical information pushing method provided by the application can be applied to an application environment shown in fig. 4. The terminal 102 communicates with the server 104 via a network, and the server 104 communicates with the prescription server 401 and the subscription server 402 via a network, respectively. The terminal 102 sends a service request message to the server 104, when the server 104 determines that the service request type of the service request message is registration inquiry, the server 104 performs conversation inquiry with the terminal 102 through a corresponding inquiry conversation template, the server 104 obtains disorder information from inquiry data in the conversation inquiry process, and finally inputs the disorder information into a disease matching model for processing, obtains a disorder information processing result and pushes the disorder information processing result to the terminal 102.
In addition, the server 104 sends the disorder information and the archive keyword to the prescription server 401, the prescription server 401 extracts the pathology keyword from the disorder information, the prescription keyword obtained by combining the pathology keyword and the archive keyword is input into a corresponding drug matching model to be matched, a prescription recommendation is generated according to the matching result and returned to the server 104, and the server 104 pushes the received prescription recommendation to the terminal 102.
When the service request type of the service request message received by the server 104 is information subscription, the service request message is sent to the subscription server 402, the subscription server 402 queries corresponding medical subscription information according to the received service request message and returns the medical subscription information to the server 104, and the server 104 pushes the medical subscription information to the terminal 102.
The prescription server 401 and the subscription server 402 may be implemented as separate servers or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 5, a medical information pushing method is provided, and the method is applied to the server 104 in fig. 4 for illustration, and includes the following steps:
s501: receiving a service request message;
s502: whether the service request type of the service request message is a registration inquiry.
The server 104 receives the service request message sent by the terminal 102, and determines whether the service request type of the service request message is a registration inquiry. When the determination result is true, S503 is executed; otherwise, S521 is performed.
S503: extracting a request keyword from the service request message;
s504: performing department matching on the request keywords and department keywords of each hospital function department, and determining corresponding hospital function departments according to department matching results;
S505: query a consultation dialogue template corresponding to a hospital functional department.
The server 104 extracts the request keywords from the service request message, removes redundant and useless information, determines the corresponding hospital functional departments according to the request keywords, and obtains the consultation dialogue templates from the corresponding hospital functional departments. By determining the hospital functional departments corresponding to the service request messages and carrying out dialogue consultation according to the consultation dialogue templates corresponding to the hospital functional departments, pertinence in the consultation dialogue and the propulsion efficiency of the consultation dialogue can be effectively improved.
S506: inquiring personal archive information of a corresponding patient in the service request message;
s507: extracting archive keywords from the personal archive information;
s508: obtaining a consultation keyword group by combining the request keyword and the file keyword;
s509: sequentially carrying out node matching on the inquiry keyword groups and all inquiry nodes in the inquiry dialogue template;
s510: taking the unmatched consultation nodes as response nodes, wherein the response nodes are initial consultation nodes when the dialogue consultation is carried out through the consultation dialogue template;
s511: responding to the service request message through the response node to conduct dialogue inquiry;
s512: and obtaining the disease information according to the question-answer data in the dialogue question-call process.
By analyzing the known information from the service request message and the personal archive information and determining the response node of the inquiry dialogue template, the problem of repeated inquiry during the inquiry dialogue can be effectively avoided, and the propulsion efficiency of the inquiry dialogue is effectively improved. In the process of carrying out dialogue inquiry through the inquiry dialogue template, the symptom information is obtained according to the inquiry data, so that the dialogue inquiry with the patient is realized.
S513: comparing the condition information with the personal profile information;
s514: when the disease information is inconsistent with the personal archive information, the personal archive information is updated according to the disease information.
And comparing the obtained disease information with personal archive information of the patient, updating the personal archive information according to inconsistent disease information, and updating the personal archive information in time to ensure the validity of the information.
S515: inputting the disease information into a corresponding disease matching model, and performing matching treatment on the disease information through the disease matching model to obtain a disease information processing result;
s516: pushing the obtained disease information processing result.
And inputting the obtained disease information into a disease matching model for matching treatment, and obtaining a disease information processing result. The server 104 sends the result of the disease information processing to the terminal 102, which can be used as reference data for diagnosis by a doctor or as a diagnosis result for a patient, so that the patient can primarily know the disease condition of the patient.
S517: extracting pathological keywords in the disease information processing result;
s518: combining the pathological keywords with the archive keywords according to preset combination conditions to obtain a prescription keyword group;
s519: inputting the prescription key word group into a corresponding drug matching model for feature matching;
s520: and generating prescription recommendation according to the drug list in the matching result, and pushing the prescription recommendation.
In addition, the server 104 sends the result of processing the disorder information and the archive keyword to the prescription server 401, the prescription server 401 extracts the pathology keyword from the disorder information, the prescription keyword obtained by combining the pathology keyword and the archive keyword is input into a corresponding drug matching model to be matched, a prescription recommendation is generated according to the matching result and returned to the server 104, and the server 104 pushes the received prescription recommendation to the terminal 102.
S521: the service request type of the service request message is information subscription;
s522: inquiring a corresponding subscription information database according to the service request message;
s523: acquiring corresponding medical subscription information from the subscription information database, and pushing the medical subscription information.
When the service request type of the service request message is information subscription, the server 104 sends the service request message to the subscription server 402, and the subscription server 402 queries corresponding medical subscription information according to the received service request message and returns the medical subscription information to the server 104, and the server 104 pushes the medical subscription information to the terminal 102.
It should be understood that, although the steps in the flowcharts of fig. 2, 3, and 5 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2-5 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily occur sequentially, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or steps.
In one embodiment, as shown in fig. 6, there is provided a medical information pushing apparatus including: a message receiving module 601, a dialogue template query module 603, a dialogue consultation module 605, a symptom information obtaining module 607, a symptom information processing module 609 and a result pushing module 611, wherein:
a message receiving module 601, configured to receive a service request message;
A dialogue template query module 603, configured to query a query dialogue template corresponding to a service request message when the service request type of the service request message is a registered query;
a dialogue consultation module 605 for responding to the service request message through a consultation dialogue template to perform dialogue consultation;
the symptom information obtaining module 607 is configured to obtain symptom information according to the question-answer data in the session question process;
the disease information processing module 609 is configured to input the disease information into a corresponding disease matching model, and perform matching processing on the disease information through the disease matching model to obtain a disease information processing result;
the result pushing module 611 is configured to push the obtained result of processing the disorder information.
According to the medical information pushing device, when the service request message of the registration inquiry service request type is received, the corresponding inquiry dialogue template is used for carrying out dialogue inquiry, then the disease information is obtained from inquiry data in the dialogue inquiry process through the disease information obtaining module, finally the disease information is input into the disease matching model through the disease information processing module for processing, the disease information processing result is obtained, and the disease information processing result is pushed through the result pushing module. The dialogue consultation is directly carried out through the consultation dialogue template, the obtained disease information is input into the corresponding disease matching model for processing, the disease information processing result is obtained and pushed, and the acquisition of the disease information and the processing process of the disease information do not need direct participation of doctors, so that repeated communication between doctors and patients is avoided, the processing process of medical service requests is simplified, and the feedback efficiency of medical information in medical service is improved.
In one embodiment, the dialogue template query module 603 includes a request keyword unit, a department determination unit, and a dialogue template acquisition unit, where: a request keyword unit for extracting a request keyword from the service request message; department determining unit for matching the request keyword with the department keyword of each hospital function department and determining the corresponding hospital function department according to the department matching result; and the dialogue template acquisition unit is used for inquiring the inquiry dialogue templates corresponding to the functional departments of the hospitals.
In one embodiment, the dialog inquiry module 605 includes a personal archive query unit, a response node determination unit, and a dialog inquiry unit, wherein: the personal archive inquiry unit is used for inquiring personal archive information of the corresponding patient in the service request message; the response node determining unit is used for determining response nodes in the inquiry dialogue template according to the service request message and the personal archive information, wherein the response nodes are initial inquiry nodes when the inquiry dialogue template is used for carrying out dialogue inquiry; and the dialogue inquiry unit is used for responding to the service request message through the response node and carrying out dialogue inquiry.
In one embodiment, the response node determination unit includes an archive keyword subunit, a keyword group subunit, a node matching subunit, and a response node subunit, wherein: a archive keyword subunit, configured to extract archive keywords from the personal archive information; a keyword group subunit, configured to combine the request keyword and the archive keyword to obtain a query keyword group; the node matching subunit is used for sequentially carrying out node matching on the inquiry keyword group and each inquiry node in the inquiry dialogue template; and the response node subunit is used for taking the unmatched inquiry node as a response node.
In one embodiment, the system further comprises an information comparison module and an archive update module, wherein: the information comparison module is used for comparing the disease information with the personal archive information; and the file updating module is used for updating the personal file information according to the disorder information when the disorder information is inconsistent with the personal file information.
In one embodiment, the system further comprises a pathology keyword module, a prescription keyword group module, a prescription matching module and a prescription pushing module, wherein: the pathological keyword module is used for extracting pathological keywords in the pathological information processing result; the prescription key phrase module is used for combining the pathological key words and the file key words according to preset combination conditions to obtain prescription key phrases; the prescription matching module is used for inputting the prescription key word group into the corresponding medicine matching model to perform characteristic matching; the prescription pushing module is used for generating prescription recommendation according to the drug list in the matching result and pushing the prescription recommendation.
In one embodiment, the subscription database query module and the subscription information pushing module are further included, wherein: the subscription database query module is used for querying a corresponding subscription information database according to the service request message when the service request type of the service request message is information subscription; the subscription information pushing module is used for acquiring corresponding medical subscription information from the subscription information database and pushing the medical subscription information.
For specific limitations of the medical information pushing device, reference may be made to the above limitation of the medical information pushing method, and no further description is given here. The modules in the medical information pushing device may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a medical information pushing method.
It will be appreciated by those skilled in the art that the structure shown in fig. 7 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of:
receiving a service request message;
when the service request type of the service request message is registration inquiry, inquiring an inquiry dialogue template corresponding to the service request message;
responding to the service request message through a consultation dialogue template to conduct dialogue consultation;
obtaining symptom information according to question-answer data in the dialogue question-call process;
inputting the disease information into a corresponding disease matching model, and performing matching treatment on the disease information through the disease matching model to obtain a disease information processing result;
pushing the obtained disease information processing result.
In one embodiment, the processor when executing the computer program further performs the steps of:
Extracting a request keyword from the service request message; performing department matching on the request keywords and department keywords of each hospital function department, and determining corresponding hospital function departments according to department matching results; query a consultation dialogue template corresponding to a hospital functional department.
In one embodiment, the processor when executing the computer program further performs the steps of:
inquiring personal archive information of a corresponding patient in the service request message; determining a response node in a consultation dialogue template according to the service request message and the personal file information, wherein the response node is an initial question node when the dialogue consultation is carried out through the consultation dialogue template; the session inquiry is performed by the responding node responding to the service request message.
In one embodiment, the processor when executing the computer program further performs the steps of:
extracting archive keywords from the personal archive information; obtaining a consultation keyword group by combining the request keyword and the file keyword; sequentially carrying out node matching on the inquiry keyword groups and all inquiry nodes in the inquiry dialogue template; and taking the unmatched inquiry node as a response node.
In one embodiment, the processor when executing the computer program further performs the steps of:
Comparing the condition information with the personal profile information; when the disease information is inconsistent with the personal archive information, the personal archive information is updated according to the disease information.
In one embodiment, the processor when executing the computer program further performs the steps of:
extracting pathological keywords in the disease information processing result; combining the pathological keywords with the archive keywords according to preset combination conditions to obtain a prescription keyword group; inputting the prescription key word group into a corresponding drug matching model for feature matching; and generating prescription recommendation according to the drug list in the matching result, and pushing the prescription recommendation.
In one embodiment, the processor when executing the computer program further performs the steps of:
when the service request type of the service request message is information subscription, inquiring a corresponding subscription information database according to the service request message; acquiring corresponding medical subscription information from the subscription information database, and pushing the medical subscription information.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
Receiving a service request message;
when the service request type of the service request message is registration inquiry, inquiring an inquiry dialogue template corresponding to the service request message;
responding to the service request message through a consultation dialogue template to conduct dialogue consultation;
obtaining symptom information according to question-answer data in the dialogue question-call process;
inputting the disease information into a corresponding disease matching model, and performing matching treatment on the disease information through the disease matching model to obtain a disease information processing result;
pushing the obtained disease information processing result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
extracting a request keyword from the service request message; performing department matching on the request keywords and department keywords of each hospital function department, and determining corresponding hospital function departments according to department matching results; query a consultation dialogue template corresponding to a hospital functional department.
In one embodiment, the computer program when executed by the processor further performs the steps of:
inquiring personal archive information of a corresponding patient in the service request message; determining a response node in a consultation dialogue template according to the service request message and the personal file information, wherein the response node is an initial question node when the dialogue consultation is carried out through the consultation dialogue template; the session inquiry is performed by the responding node responding to the service request message.
In one embodiment, the computer program when executed by the processor further performs the steps of:
extracting archive keywords from the personal archive information; obtaining a consultation keyword group by combining the request keyword and the file keyword; sequentially carrying out node matching on the inquiry keyword groups and all inquiry nodes in the inquiry dialogue template; and taking the unmatched inquiry node as a response node.
In one embodiment, the computer program when executed by the processor further performs the steps of:
comparing the condition information with the personal profile information; when the disease information is inconsistent with the personal archive information, the personal archive information is updated according to the disease information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
extracting pathological keywords in the disease information processing result; combining the pathological keywords with the archive keywords according to preset combination conditions to obtain a prescription keyword group; inputting the prescription key word group into a corresponding drug matching model for feature matching; and generating prescription recommendation according to the drug list in the matching result, and pushing the prescription recommendation.
In one embodiment, the computer program when executed by the processor further performs the steps of:
When the service request type of the service request message is information subscription, inquiring a corresponding subscription information database according to the service request message; acquiring corresponding medical subscription information from the subscription information database, and pushing the medical subscription information.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. A medical information pushing method, the method comprising:
receiving a service request message;
when the service request type of the service request message is registration inquiry, inquiring an inquiry dialogue template corresponding to a hospital function department matched with the service request message;
inquiring personal archive information of a corresponding patient in the service request message;
Extracting archive keywords from the personal archive information;
according to preset combination conditions, combining the request keywords in the service request message with the file keywords to obtain inquiry keyword groups;
sequentially carrying out node matching on the inquiry keyword group and each inquiry node in the inquiry dialogue template;
taking the unmatched inquiry node as a response node; the response node is an initial questioning node when the questioning dialogue template is used for carrying out dialogue questioning;
responding to the service request message through the response node, and performing dialogue inquiry;
obtaining symptom information according to question-answer data in the dialogue question-call process;
inputting the disease information into a corresponding disease matching model, and performing matching processing on the disease information through the disease matching model to obtain a disease information processing result;
pushing the obtained disease information processing result.
2. The method of claim 1, wherein the step of querying a corresponding inquiry dialogue template in a hospital functional department that matches the service request message comprises:
extracting a request keyword from the service request message;
Performing department matching on the request keywords and department keywords of each hospital function department, and determining the corresponding hospital function department according to department matching results;
and inquiring a consultation dialogue template corresponding to the hospital functional department.
3. The method of claim 1, wherein the personal profile information includes at least one of registration information and health profile information; the registration information comprises reservation information recorded in the registration medical system when the corresponding patient is registered; the health profile information includes profile data established by the healthcare system for registered patients.
4. The method of claim 1, wherein said extracting profile keywords from said personal profile information comprises:
and extracting archive keywords from the personal archive information based on a TextRank keyword extraction algorithm.
5. The method of claim 1, further comprising, after the step of obtaining the condition information from the question-answer data in the session inquiry process:
comparing the condition information with the personal profile information;
and when the disease information is inconsistent with the personal archive information, updating the personal archive information according to the disease information.
6. The method according to claim 1, further comprising, after the step of pushing the obtained result of the disorder information processing, the step of:
extracting pathological keywords in the disease information processing result;
combining the pathological keywords with the archive keywords according to preset combination conditions to obtain a prescription keyword group;
inputting the prescription key word group into a corresponding drug matching model for feature matching;
and generating prescription recommendation according to the drug list in the matching result, and pushing the prescription recommendation.
7. The method according to any one of claims 1 to 6, further comprising:
when the service request type of the service request message is information subscription, inquiring a corresponding subscription information database according to the service request message;
acquiring corresponding medical subscription information from the subscription information database, and pushing the medical subscription information.
8. A medical information pushing apparatus, characterized in that the apparatus comprises:
a message receiving module for receiving a service request message;
the dialogue template inquiry module is used for inquiring a corresponding consultation dialogue template in a hospital functional department matched with the service request message when the service request type of the service request message is registration consultation;
The dialogue inquiry module is used for inquiring personal archive information of a corresponding patient in the service request message; extracting archive keywords from the personal archive information; according to preset combination conditions, combining the request keywords in the service request message with the file keywords to obtain inquiry keyword groups; sequentially carrying out node matching on the inquiry keyword group and each inquiry node in the inquiry dialogue template; taking the unmatched inquiry node as a response node; the response node is an initial questioning node when the questioning dialogue template is used for carrying out dialogue questioning; responding to the service request message through the response node, and performing dialogue inquiry;
the disease information acquisition module is used for acquiring disease information according to question-answer data in the dialogue question-call process;
the disease information processing module is used for inputting the disease information into a corresponding disease matching model, and carrying out matching processing on the disease information through the disease matching model to obtain a disease information processing result;
and the result pushing module is used for pushing the obtained disease information processing result.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
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| CN106777971A (en) * | 2016-12-15 | 2017-05-31 | 杭州卓健信息科技有限公司 | A kind of intelligent hospital guide's method and its device |
| CN107480450A (en) * | 2017-08-15 | 2017-12-15 | 京东方科技集团股份有限公司 | A kind of intelligence point examines method and system |
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