CN111986771A - Medical prescription query method and device, electronic equipment and storage medium - Google Patents
Medical prescription query method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN111986771A CN111986771A CN202010917922.4A CN202010917922A CN111986771A CN 111986771 A CN111986771 A CN 111986771A CN 202010917922 A CN202010917922 A CN 202010917922A CN 111986771 A CN111986771 A CN 111986771A
- Authority
- CN
- China
- Prior art keywords
- query
- medical
- request
- determining
- prescription
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 37
- 230000015654 memory Effects 0.000 claims description 23
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000004458 analytical method Methods 0.000 claims description 6
- 239000000284 extract Substances 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 abstract description 2
- 239000002775 capsule Substances 0.000 description 12
- RTXOFQZKPXMALH-GHXIOONMSA-N cefdinir Chemical group S1C(N)=NC(C(=N\O)\C(=O)N[C@@H]2C(N3C(=C(C=C)CS[C@@H]32)C(O)=O)=O)=C1 RTXOFQZKPXMALH-GHXIOONMSA-N 0.000 description 12
- 229960003719 cefdinir Drugs 0.000 description 12
- 206010037660 Pyrexia Diseases 0.000 description 9
- BSYNRYMUTXBXSQ-UHFFFAOYSA-N Aspirin Chemical compound CC(=O)OC1=CC=CC=C1C(O)=O BSYNRYMUTXBXSQ-UHFFFAOYSA-N 0.000 description 8
- 206010068319 Oropharyngeal pain Diseases 0.000 description 8
- 201000007100 Pharyngitis Diseases 0.000 description 8
- 229960001138 acetylsalicylic acid Drugs 0.000 description 8
- 230000006870 function Effects 0.000 description 7
- 208000036071 Rhinorrhea Diseases 0.000 description 6
- 206010039101 Rhinorrhoea Diseases 0.000 description 6
- 208000021760 high fever Diseases 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 238000010276 construction Methods 0.000 description 4
- 230000001960 triggered effect Effects 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 238000000605 extraction Methods 0.000 description 3
- 230000001737 promoting effect Effects 0.000 description 3
- 241001619326 Cephalosporium Species 0.000 description 2
- 206010020751 Hypersensitivity Diseases 0.000 description 2
- 208000024780 Urticaria Diseases 0.000 description 2
- 208000026935 allergic disease Diseases 0.000 description 2
- 230000007815 allergy Effects 0.000 description 2
- 238000013500 data storage Methods 0.000 description 2
- 208000002173 dizziness Diseases 0.000 description 2
- 229940079593 drug Drugs 0.000 description 2
- 239000003814 drug Substances 0.000 description 2
- 208000001780 epistaxis Diseases 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
- G06F16/3344—Query execution using natural language analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Computational Linguistics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Chemical & Material Sciences (AREA)
- Evolutionary Biology (AREA)
- Databases & Information Systems (AREA)
- Bioinformatics & Computational Biology (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Computation (AREA)
- Medicinal Chemistry (AREA)
- Epidemiology (AREA)
- Medical Informatics (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention relates to intelligent medical treatment and provides a medical prescription query method, a medical prescription query device, electronic equipment and a storage medium. The method can extract a plurality of medical query objects from a medical prescription query request when the medical prescription query request is received, determine the fields of the medical query objects, determine a target database according to the fields, generate a plurality of medical query words according to the medical query objects, search the target database by using the medical query words to obtain a plurality of query results, calculate the similarity between each query result and the medical query words, and determine the query result with the highest similarity as the target result of the medical prescription query request. The invention can improve the data query speed. In addition, the invention also relates to a block chain technology, and the target result can be stored in the block chain.
Description
Technical Field
The invention relates to the technical field of intelligent medical treatment, in particular to a medical prescription query method, a medical prescription query device, electronic equipment and a storage medium.
Background
With the development of information networks, more and more data are generated by various industries. Massive time series data exists in many fields, for example: medical field, biological field, etc. When data are acquired from a multidimensional data system, the data query speed is low due to the fact that the data volume in the data system is large and multiple dimensions are complicated, and user experience is reduced.
Disclosure of Invention
In view of the above, there is a need to provide a medical prescription query method, device, electronic device and storage medium, which can improve the data query speed and further improve the user experience.
In one aspect, the present invention provides a medical prescription query method, including:
when a medical prescription query request is received, extracting a plurality of medical query objects from the medical prescription query request;
determining the fields to which the medical query objects belong, and determining a target database according to the fields;
generating a plurality of medical query terms according to the plurality of medical query objects;
searching the target database by using the medical query words to obtain a plurality of query results;
calculating the similarity of each query result and the plurality of medical query terms;
and determining the query result with the highest similarity as the target result of the medical prescription query request.
According to a preferred embodiment of the present invention, the extracting the plurality of medical query objects from the medical prescription query request comprises:
determining a request type to which the medical prescription query request belongs;
determining a target thread from a preset thread pool according to the request type;
analyzing a request body of the medical prescription query request by using the target thread to obtain request information carried by the medical prescription query request;
acquiring a preset label from a configuration label table, wherein the preset label is a label defined in advance;
and acquiring information corresponding to the preset label from the request information as the plurality of medical query objects.
According to a preferred embodiment of the present invention, the searching the target database using the plurality of medical query terms to obtain a plurality of query results comprises:
determining a vocabulary quantity of the plurality of medical query terms;
acquiring a plurality of idle threads with the number being the vocabulary number from the preset thread pool;
searching the plurality of medical query terms from the target database by using the plurality of idle threads respectively to obtain data results corresponding to the plurality of medical query terms;
and determining the intersection of the data results corresponding to the plurality of medical query terms to obtain the plurality of query results.
According to a preferred embodiment of the present invention, the determining the domain to which the plurality of medical query subjects belong and the determining the target database according to the domain comprises:
performing semantic analysis on the plurality of medical query objects to obtain characteristic information;
determining a scene matched with the feature information as the field;
determining a target identification of the domain;
and determining the database with the target identification as the target database.
According to a preferred embodiment of the present invention, the generating a plurality of medical query terms from the plurality of medical query subjects comprises:
acquiring a preset vocabulary matched with each medical query object from a preset medical vocabulary table;
when the number of the preset words of each medical query object is multiple, acquiring the query frequency of the preset words;
and determining the preset vocabulary with the maximum query frequency as the medical query word of each medical query object to obtain the plurality of medical query words corresponding to the plurality of medical query objects.
According to a preferred embodiment of the present invention, the calculating the similarity of each query result to the plurality of medical query terms comprises:
acquiring data characteristics of each query result;
calculating the similarity of each data feature and each medical query word by using a distance formula to obtain a plurality of first similarities of each data feature;
acquiring a first similarity with the maximum similarity from the plurality of first similarities as the feature similarity of each data feature;
and performing addition operation on the feature similarity of each data feature to obtain the similarity of each query result and the plurality of medical query words.
According to a preferred embodiment of the present invention, after determining the query result with the highest similarity as the target result of the medical prescription query request, the method further comprises:
acquiring a sending terminal of the medical prescription query request, and acquiring a request identifier of the medical prescription query request;
generating prompt information according to the request identification and the target result;
and sending the prompt information to the sending terminal.
In another aspect, the present invention further provides a medical prescription query apparatus, including:
the medical prescription query unit is used for receiving a medical prescription query request, and extracting a plurality of medical query objects from the medical prescription query request;
the determining unit is used for determining the fields of the medical query objects and determining a target database according to the fields;
the generating unit is used for generating a plurality of medical query terms according to the plurality of medical query objects;
the searching unit is used for searching the target database by using the plurality of medical query terms to obtain a plurality of query results;
the calculation unit is used for calculating the similarity between each query result and the plurality of medical query terms;
the determining unit is further configured to determine the query result with the highest similarity as the target result of the medical prescription query request.
In another aspect, the present invention further provides an electronic device, including:
a memory storing computer readable instructions; and
a processor executing computer readable instructions stored in the memory to implement the medical prescription query method.
In another aspect, the present invention also provides a computer-readable storage medium having computer-readable instructions stored therein, which are executed by a processor in an electronic device to implement the medical prescription query method.
According to the technical scheme, when a medical prescription query request is received, the medical prescription query request can be used for extracting a plurality of medical query objects from the medical prescription query request, determining the fields to which the medical query objects belong, determining the target database according to the fields, directly querying the target result from the target database by determining the target database, improving the query efficiency, generating a plurality of medical query terms according to the medical query objects, reducing the range of the query results by generating the medical query terms so as to improve the determination efficiency of the target result, searching the target database by using the medical query terms to obtain a plurality of query results, calculating the similarity between each query result and the medical query terms, and determining the query result with the highest similarity as the target result of the medical prescription query request, by analyzing the similarity between the query result and the plurality of medical query words, the target result can be accurately obtained. The medical prescription query request acquisition method and the medical prescription query request acquisition device can accurately acquire the target result of the medical prescription query request from a database with huge data volume and large dimensionality, and can improve the acquisition efficiency of the target result because the query results of a plurality of medical query objects are processed without analyzing the medical query objects one by one. The invention is also applied to intelligent medical scenes, thereby promoting the construction of intelligent cities.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of the medical prescription query method of the present invention.
FIG. 2 is a functional block diagram of a medical prescription query device according to a preferred embodiment of the present invention.
Fig. 3 is a schematic structural diagram of an electronic device for implementing a medical prescription query method according to a preferred embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
Fig. 1 is a flow chart of a medical prescription query method according to a preferred embodiment of the present invention. The order of the steps in the flow chart may be changed and some steps may be omitted according to different needs.
The medical prescription query method is applied to an intelligent medical scene, so that the construction of an intelligent city is promoted. The medical prescription query method is applied to one or more electronic devices, which are devices capable of automatically performing numerical calculation and/or information processing according to computer readable instructions set or stored in advance, and the hardware thereof includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.
The electronic device may be any electronic product capable of performing human-computer interaction with a user, for example, a Personal computer, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), a game machine, an interactive Internet Protocol Television (IPTV), a smart wearable device, and the like.
The electronic device may include a network device and/or a user device. Wherein the network device includes, but is not limited to, a single network electronic device, an electronic device group consisting of a plurality of network electronic devices, or a Cloud Computing (Cloud Computing) based Cloud consisting of a large number of hosts or network electronic devices.
The network in which the electronic device is located includes, but is not limited to: the internet, a wide area Network, a metropolitan area Network, a local area Network, a Virtual Private Network (VPN), and the like.
S10, when a medical prescription query request is received, extracting a plurality of medical query objects from the medical prescription query request.
In at least one embodiment of the present invention, the medical prescription query request may be triggered by a doctor, and the medical prescription query request may also be triggered by a supervisor, and the triggering user of the medical prescription query request is not limited by the present invention.
Further, the request information carried by the medical prescription inquiry request includes, but is not limited to: the plurality of medical query subjects.
In at least one embodiment of the invention, the plurality of medical query subjects may be diagnostic keywords of the medical prescription request that trigger user input. For example, the plurality of medical query subjects may be a cold, dizziness, cephalosporium, and the like.
In at least one embodiment of the invention, the electronic device extracting a plurality of medical query objects from the medical prescription query request comprises:
determining a request type to which the medical prescription query request belongs;
determining a target thread from a preset thread pool according to the request type;
analyzing a request body of the medical prescription query request by using the target thread to obtain request information carried by the medical prescription query request;
acquiring a preset label from a configuration label table, wherein the preset label is a label defined in advance;
and acquiring information corresponding to the preset label from the request information as the plurality of medical query objects.
Wherein, a plurality of tags are stored in the configuration tag table, and the tags stored in the configuration tag table include, but are not limited to: ID. name, num, etc.
By analyzing the request body without analyzing the whole request of the medical prescription query request, the analysis efficiency can be improved, and the plurality of medical query objects can be accurately acquired from the request information by utilizing the mapping relation between the preset label and the query object.
S11, determining the fields to which the medical query objects belong, and determining a target database according to the fields.
In at least one embodiment of the present invention, the field may be a medical field, a financial field, or the like.
In at least one embodiment of the present invention, the target database refers to a database corresponding to the domain. For example, when the field is a medical field, the target database may be a database storing medical prescriptions and drug amounts.
In at least one embodiment of the present invention, the electronic device determining a domain to which the plurality of medical query subjects belong and determining a target database according to the domain comprises:
performing semantic analysis on the plurality of medical query objects to obtain characteristic information;
determining a scene matched with the feature information as the field;
determining a target identification of the domain;
and determining the database with the target identification as the target database.
Wherein the target identifier may be YL.
By extracting the context characteristics of the medical query objects, the characteristic information can be generated quickly, the field can be accurately determined by utilizing the characteristic information, and the target database can be accurately determined by utilizing the target identification of the field.
S12, generating a plurality of medical query terms according to the medical query objects.
In at least one embodiment of the present invention, the plurality of medical query terms are obtained from a preset medical vocabulary according to the plurality of medical query subjects. Further, the preset medical vocabulary table stores the full names of the plurality of medical query objects. For example: the medical query object is a cefdinir capsule, and correspondingly, the medical query word is a cefdinir capsule.
Further, each medical query object corresponds to one medical query term.
In at least one embodiment of the present invention, the electronic device generating a plurality of medical query terms from the plurality of medical query objects comprises:
acquiring a preset vocabulary matched with each medical query object from a preset medical vocabulary table;
when the number of the preset words of each medical query object is multiple, acquiring the query frequency of the preset words;
and determining the preset vocabulary with the maximum query frequency as the medical query word of each medical query object to obtain the plurality of medical query words corresponding to the plurality of medical query objects.
The plurality of medical query terms can be quickly generated through query frequency.
In at least one embodiment of the invention, by generating the medical query term, the range of the plurality of query results can be narrowed to improve the determination efficiency of the target result.
S13, searching the target database by using the medical query words to obtain a plurality of query results.
In at least one embodiment of the present invention, the plurality of medical query terms are included in each query result.
In at least one embodiment of the present invention, the electronic device searches the target database using the plurality of medical query terms, and obtaining a plurality of query results includes:
determining a vocabulary quantity of the plurality of medical query terms;
acquiring a plurality of idle threads with the number being the vocabulary number from the preset thread pool;
searching the plurality of medical query terms from the target database by using the plurality of idle threads respectively to obtain data results corresponding to the plurality of medical query terms;
and determining the intersection of the data results corresponding to the plurality of medical query terms to obtain the plurality of query results.
For example: the medical query terms are cefdinir capsules and aspirin, so that the number of the vocabularies is 2, 2 corresponding idle threads are obtained from a preset thread pool and are respectively thread 1 and thread 2, the thread 1 is used for searching the cefdinir capsules from the target database to obtain data results corresponding to the cefdinir capsules, the data results comprise a table A, a table B and a table C, the thread 2 is used for searching the aspirin from the target database to obtain nominal data results corresponding to the aspirin, the data results comprise a table B, a table C and a table D, the intersection of the data results of the cefdinir capsules and the data results of the aspirin is determined, and a plurality of query results are obtained, namely: table B, table C.
Through a plurality of idle threads, the data result can be quickly obtained from the target database, and then the plurality of query results can be accurately determined according to the intersection relation of the data result.
And S14, calculating the similarity of each query result and the plurality of medical query words.
It will be appreciated that the number of data features in each query result is generally different from the number of the plurality of medical query terms.
In at least one embodiment of the present invention, the electronic device calculating the similarity of each query result to the plurality of medical query terms comprises:
acquiring data characteristics of each query result;
calculating the similarity of each data feature and each medical query word by using a distance formula to obtain a plurality of first similarities of each data feature;
acquiring a first similarity with the maximum similarity from the plurality of first similarities as the feature similarity of each data feature;
and performing addition operation on the feature similarity of each data feature to obtain the similarity of each query result and the plurality of medical query words.
Wherein, the data characteristics refer to medical characteristic words.
For example: the plurality of medical query terms includes: the query result 1 contains the following data characteristics: cold, fever, sore throat; the data characteristics contained in the query result 2 include nosebleed, excessive internal heat, allergy and urticaria. For the query result 1, the similarity of the cold and the rhinorrhea is calculated to be 0.8, the similarity of the cold and the high fever is 0.5, the similarity of the fever and the rhinorrhea is 0.7, the similarity of the fever and the high fever is 0.9, the similarity of sore throat and the rhinorrhea is 0.3, and the similarity of sore throat and the high fever is 0.4, the electronic equipment determines that the similarity of the cold characteristic is 0.8, the similarity of the fever is 0.9, and the similarity of the sore throat is 0.4, and further determines that the similarity of the query result 1 and the medical query words is 0.8+0.9+ 0.4-2.1. Similarly, the similarity between the query result 2 and the plurality of medical query terms can be calculated.
Through the above embodiment, on the premise that the number of the data features in the query result is different from the number of the plurality of medical query terms, the similarity between each query result and the plurality of medical query terms can be calculated.
In other embodiments, because the dimensions of the data features are the same as the dimensions of the medical query terms, the electronic device can calculate the similarity of each data feature to each medical query term using a distance formula.
And S15, determining the query result with the highest similarity as the target result of the medical prescription query request.
It is emphasized that the target result can also be stored in a node of a blockchain in order to further ensure the privacy and security of the target result.
In at least one embodiment of the present invention, the target result refers to a query result having the highest similarity with the plurality of medical query terms.
In at least one embodiment of the invention, after determining the query result with the highest similarity as the target result of the medical prescription query request, the method further comprises:
acquiring a sending terminal of the medical prescription query request, and acquiring a request identifier of the medical prescription query request;
generating prompt information according to the request identification and the target result;
and sending the prompt information to the sending terminal.
Wherein the sending terminal may be a terminal device of the triggering user of the medical prescription query request.
By the implementation mode, the target result can be sent to the sending terminal in time when the target result is obtained.
According to the technical scheme, when a medical prescription query request is received, the medical prescription query request can be used for extracting a plurality of medical query objects from the medical prescription query request, determining the fields to which the medical query objects belong, determining the target database according to the fields, directly querying the target result from the target database by determining the target database, improving the query efficiency, generating a plurality of medical query terms according to the medical query objects, reducing the range of the query results by generating the medical query terms so as to improve the determination efficiency of the target result, searching the target database by using the medical query terms to obtain a plurality of query results, calculating the similarity between each query result and the medical query terms, and determining the query result with the highest similarity as the target result of the medical prescription query request, by analyzing the similarity between the query result and the plurality of medical query words, the target result can be accurately obtained. The medical prescription query request acquisition method and the medical prescription query request acquisition device can accurately acquire the target result of the medical prescription query request from a database with huge data volume and large dimensionality, and can improve the acquisition efficiency of the target result because the query results of a plurality of medical query objects are processed without analyzing the medical query objects one by one. The invention is also applied to intelligent medical scenes, thereby promoting the construction of intelligent cities.
FIG. 2 is a functional block diagram of a medical prescription query device according to a preferred embodiment of the present invention. The medical prescription inquiry apparatus 11 includes an extraction unit 110, a determination unit 111, a generation unit 112, a search unit 113, a calculation unit 114, an acquisition unit 115, and a transmission unit 116. The module/unit referred to herein is a series of computer readable instruction segments that can be accessed by the processor 13 and perform a fixed function and that are stored in the memory 12. In the present embodiment, the functions of the modules/units will be described in detail in the following embodiments.
When a medical prescription query request is received, the extraction unit 110 extracts a plurality of medical query objects from the medical prescription query request.
In at least one embodiment of the present invention, the medical prescription query request may be triggered by a doctor, and the medical prescription query request may also be triggered by a supervisor, and the triggering user of the medical prescription query request is not limited by the present invention.
Further, the request information carried by the medical prescription inquiry request includes, but is not limited to: the plurality of medical query subjects.
In at least one embodiment of the invention, the plurality of medical query subjects may be diagnostic keywords of the medical prescription request that trigger user input. For example, the plurality of medical query subjects may be a cold, dizziness, cephalosporium, and the like.
In at least one embodiment of the present invention, the extracting unit 110 extracts a plurality of medical query objects from the medical prescription query request includes:
determining a request type to which the medical prescription query request belongs;
determining a target thread from a preset thread pool according to the request type;
analyzing a request body of the medical prescription query request by using the target thread to obtain request information carried by the medical prescription query request;
acquiring a preset label from a configuration label table, wherein the preset label is a label defined in advance;
and acquiring information corresponding to the preset label from the request information as the plurality of medical query objects.
Wherein, a plurality of tags are stored in the configuration tag table, and the tags stored in the configuration tag table include, but are not limited to: ID. name, num, etc.
By analyzing the request body without analyzing the whole request of the medical prescription query request, the analysis efficiency can be improved, and the plurality of medical query objects can be accurately acquired from the request information by utilizing the mapping relation between the preset label and the query object.
The determination unit 111 determines a domain to which the plurality of medical query subjects belong, and determines a target database according to the domain.
In at least one embodiment of the present invention, the field may be a medical field, a financial field, or the like.
In at least one embodiment of the present invention, the target database refers to a database corresponding to the domain. For example, when the field is a medical field, the target database may be a database storing medical prescriptions and drug amounts.
In at least one embodiment of the present invention, the determining unit 111 determines a domain to which the plurality of medical query subjects belong, and determining the target database according to the domain includes:
performing semantic analysis on the plurality of medical query objects to obtain characteristic information;
determining a scene matched with the feature information as the field;
determining a target identification of the domain;
and determining the database with the target identification as the target database.
Wherein the target identifier may be YL.
By extracting the context characteristics of the medical query objects, the characteristic information can be generated quickly, the field can be accurately determined by utilizing the characteristic information, and the target database can be accurately determined by utilizing the target identification of the field.
The generating unit 112 generates a plurality of medical query terms from the plurality of medical query objects.
In at least one embodiment of the present invention, the plurality of medical query terms are obtained from a preset medical vocabulary according to the plurality of medical query subjects. Further, the preset medical vocabulary table stores the full names of the plurality of medical query objects. For example: the medical query object is a cefdinir capsule, and correspondingly, the medical query word is a cefdinir capsule.
Further, each medical query object corresponds to one medical query term.
In at least one embodiment of the present invention, the generating unit 112 generates a plurality of medical query terms from the plurality of medical query objects includes:
acquiring a preset vocabulary matched with each medical query object from a preset medical vocabulary table;
when the number of the preset words of each medical query object is multiple, acquiring the query frequency of the preset words;
and determining the preset vocabulary with the maximum query frequency as the medical query word of each medical query object to obtain the plurality of medical query words corresponding to the plurality of medical query objects.
The plurality of medical query terms can be quickly generated through query frequency.
In at least one embodiment of the invention, by generating the medical query term, the range of the plurality of query results can be narrowed to improve the determination efficiency of the target result.
The search unit 113 searches the target database using the plurality of medical query terms to obtain a plurality of query results.
In at least one embodiment of the present invention, the plurality of medical query terms are included in each query result.
In at least one embodiment of the present invention, the searching unit 113 searches the target database using the plurality of medical query terms, and obtaining a plurality of query results includes:
determining a vocabulary quantity of the plurality of medical query terms;
acquiring a plurality of idle threads with the number being the vocabulary number from the preset thread pool;
searching the plurality of medical query terms from the target database by using the plurality of idle threads respectively to obtain data results corresponding to the plurality of medical query terms;
and determining the intersection of the data results corresponding to the plurality of medical query terms to obtain the plurality of query results.
For example: the medical query terms are cefdinir capsules and aspirin, so that the number of the vocabularies is 2, 2 corresponding idle threads are obtained from a preset thread pool and are respectively thread 1 and thread 2, the thread 1 is used for searching the cefdinir capsules from the target database to obtain data results corresponding to the cefdinir capsules, the data results comprise a table A, a table B and a table C, the thread 2 is used for searching the aspirin from the target database to obtain nominal data results corresponding to the aspirin, the data results comprise a table B, a table C and a table D, the intersection of the data results of the cefdinir capsules and the data results of the aspirin is determined, and a plurality of query results are obtained, namely: table B, table C.
Through a plurality of idle threads, the data result can be quickly obtained from the target database, and then the plurality of query results can be accurately determined according to the intersection relation of the data result.
The calculation unit 114 calculates the similarity of each query result to the plurality of medical query terms.
It will be appreciated that the number of data features in each query result is generally different from the number of the plurality of medical query terms.
In at least one embodiment of the present invention, the calculating unit 114 calculates the similarity between each query result and the plurality of medical query terms includes:
acquiring data characteristics of each query result;
calculating the similarity of each data feature and each medical query word by using a distance formula to obtain a plurality of first similarities of each data feature;
acquiring a first similarity with the maximum similarity from the plurality of first similarities as the feature similarity of each data feature;
and performing addition operation on the feature similarity of each data feature to obtain the similarity of each query result and the plurality of medical query words.
Wherein, the data characteristics refer to medical characteristic words.
For example: the plurality of medical query terms includes: the query result 1 contains the following data characteristics: cold, fever, sore throat; the data characteristics contained in the query result 2 include nosebleed, excessive internal heat, allergy and urticaria. For the query result 1, the similarity between the cold and the rhinorrhea is calculated to be 0.8, the similarity between the cold and the high fever is 0.5, the similarity between the fever and the rhinorrhea is 0.7, the similarity between the fever and the high fever is 0.9, the similarity between the sore throat and the rhinorrhea is 0.3, the similarity between the sore throat and the high fever is 0.4, the calculating unit 114 determines that the similarity between the cold and the fever is 0.8, the similarity between the fever and the sore throat is 0.9, and the similarity between the query result 1 and the plurality of medical query words is 0.8+0.9+ 0.4-2.1. Similarly, the similarity between the query result 2 and the plurality of medical query terms can be calculated.
Through the above embodiment, on the premise that the number of the data features in the query result is different from the number of the plurality of medical query terms, the similarity between each query result and the plurality of medical query terms can be calculated.
In other embodiments, since the dimension of the data feature is the same as the dimension of the medical query term, the calculation unit 114 can calculate the similarity of each data feature to each medical query term using a distance formula.
The determination unit 111 determines the query result with the highest similarity as the target result of the medical prescription query request.
It is emphasized that the target result can also be stored in a node of a blockchain in order to further ensure the privacy and security of the target result.
In at least one embodiment of the present invention, the target result refers to a query result having the highest similarity with the plurality of medical query terms.
In at least one embodiment of the present invention, after determining the query result with the highest similarity as the target result of the medical prescription query request, the obtaining unit 115 obtains the sending terminal of the medical prescription query request, and obtains the request identifier of the medical prescription query request;
the generating unit 112 generates a prompt message according to the request identifier and the target result;
the sending unit 116 sends the prompt information to the sending terminal.
Wherein the sending terminal may be a terminal device of the triggering user of the medical prescription query request.
By the implementation mode, the target result can be sent to the sending terminal in time when the target result is obtained.
According to the technical scheme, when a medical prescription query request is received, the medical prescription query request can be used for extracting a plurality of medical query objects from the medical prescription query request, determining the fields to which the medical query objects belong, determining the target database according to the fields, directly querying the target result from the target database by determining the target database, improving the query efficiency, generating a plurality of medical query terms according to the medical query objects, reducing the range of the query results by generating the medical query terms so as to improve the determination efficiency of the target result, searching the target database by using the medical query terms to obtain a plurality of query results, calculating the similarity between each query result and the medical query terms, and determining the query result with the highest similarity as the target result of the medical prescription query request, by analyzing the similarity between the query result and the plurality of medical query words, the target result can be accurately obtained. The medical prescription query request acquisition method and the medical prescription query request acquisition device can accurately acquire the target result of the medical prescription query request from a database with huge data volume and large dimensionality, and can improve the acquisition efficiency of the target result because the query results of a plurality of medical query objects are processed without analyzing the medical query objects one by one. The invention is also applied to intelligent medical scenes, thereby promoting the construction of intelligent cities.
Fig. 3 is a schematic structural diagram of an electronic device for implementing a medical prescription query method according to a preferred embodiment of the present invention.
In one embodiment of the present invention, the electronic device 1 includes, but is not limited to, a memory 12, a processor 13, and computer readable instructions, such as a medical prescription query program, stored in the memory 12 and executable on the processor 13.
It will be appreciated by a person skilled in the art that the schematic diagram is only an example of the electronic device 1 and does not constitute a limitation of the electronic device 1, and that it may comprise more or less components than shown, or some components may be combined, or different components, e.g. the electronic device 1 may further comprise an input output device, a network access device, a bus, etc.
The Processor 13 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The processor 13 is an operation core and a control center of the electronic device 1, and is connected to each part of the whole electronic device 1 by various interfaces and lines, and executes an operating system of the electronic device 1 and various installed application programs, program codes, and the like.
Illustratively, the computer readable instructions may be partitioned into one or more modules/units that are stored in the memory 12 and executed by the processor 13 to implement the present invention. The one or more modules/units may be a series of computer readable instruction segments capable of performing specific functions, which are used for describing the execution process of the computer readable instructions in the electronic device 1. For example, the computer-readable instructions may be divided into an extraction unit 110, a determination unit 111, a generation unit 112, a search unit 113, a calculation unit 114, an acquisition unit 115, and a transmission unit 116.
The memory 12 may be used for storing the computer readable instructions and/or modules, and the processor 13 implements various functions of the electronic device 1 by executing or executing the computer readable instructions and/or modules stored in the memory 12 and invoking data stored in the memory 12. The memory 12 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to use of the electronic device, and the like. The memory 12 may include non-volatile and volatile memories, such as: a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other storage device.
The memory 12 may be an external memory and/or an internal memory of the electronic device 1. Further, the memory 12 may be a memory having a physical form, such as a memory stick, a TF Card (Trans-flash Card), or the like.
The integrated modules/units of the electronic device 1 may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the flow of the method according to the above embodiments may be implemented by hardware that is configured to be instructed by computer readable instructions, which may be stored in a computer readable storage medium, and when the computer readable instructions are executed by a processor, the steps of the method embodiments may be implemented.
Wherein the computer readable instructions comprise computer readable instruction code which may be in source code form, object code form, an executable file or some intermediate form, and the like. The computer-readable medium may include: any entity or device capable of carrying said computer readable instruction code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM).
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
With reference to fig. 1, the memory 12 of the electronic device 1 stores computer-readable instructions to implement a medical prescription query method, and the processor 13 can execute the computer-readable instructions to implement:
when a medical prescription query request is received, extracting a plurality of medical query objects from the medical prescription query request;
determining the fields to which the medical query objects belong, and determining a target database according to the fields;
generating a plurality of medical query terms according to the plurality of medical query objects;
searching the target database by using the medical query words to obtain a plurality of query results;
calculating the similarity of each query result and the plurality of medical query terms;
and determining the query result with the highest similarity as the target result of the medical prescription query request.
Specifically, the processor 13 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the computer readable instructions, which is not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The computer readable storage medium has computer readable instructions stored thereon, wherein the computer readable instructions when executed by the processor 13 are configured to implement the steps of:
when a medical prescription query request is received, extracting a plurality of medical query objects from the medical prescription query request;
determining the fields to which the medical query objects belong, and determining a target database according to the fields;
generating a plurality of medical query terms according to the plurality of medical query objects;
searching the target database by using the medical query words to obtain a plurality of query results;
calculating the similarity of each query result and the plurality of medical query terms;
and determining the query result with the highest similarity as the target result of the medical prescription query request.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A medical prescription query method, comprising:
when a medical prescription query request is received, extracting a plurality of medical query objects from the medical prescription query request;
determining the fields to which the medical query objects belong, and determining a target database according to the fields;
generating a plurality of medical query terms according to the plurality of medical query objects;
searching the target database by using the medical query words to obtain a plurality of query results;
calculating the similarity of each query result and the plurality of medical query terms;
and determining the query result with the highest similarity as the target result of the medical prescription query request.
2. The medical prescription query method of claim 1, wherein said extracting a plurality of medical query objects from the medical prescription query request comprises:
determining a request type to which the medical prescription query request belongs;
determining a target thread from a preset thread pool according to the request type;
analyzing a request body of the medical prescription query request by using the target thread to obtain request information carried by the medical prescription query request;
acquiring a preset label from a configuration label table, wherein the preset label is a label defined in advance;
and acquiring information corresponding to the preset label from the request information as the plurality of medical query objects.
3. The medical prescription query method of claim 2, wherein said searching the target database using the plurality of medical query terms to obtain a plurality of query results comprises:
determining a vocabulary quantity of the plurality of medical query terms;
acquiring a plurality of idle threads with the number being the vocabulary number from the preset thread pool;
searching the plurality of medical query terms from the target database by using the plurality of idle threads respectively to obtain data results corresponding to the plurality of medical query terms;
and determining the intersection of the data results corresponding to the plurality of medical query terms to obtain the plurality of query results.
4. The medical prescription query method of claim 1, wherein said determining a domain to which the plurality of medical query subjects belong and determining a target database from the domain comprises:
performing semantic analysis on the plurality of medical query objects to obtain characteristic information;
determining a scene matched with the feature information as the field;
determining a target identification of the domain;
and determining the database with the target identification as the target database.
5. The medical prescription query method of claim 1, wherein said generating a plurality of medical query terms from the plurality of medical query subjects comprises:
acquiring a preset vocabulary matched with each medical query object from a preset medical vocabulary table;
when the number of the preset words of each medical query object is multiple, acquiring the query frequency of the preset words;
and determining the preset vocabulary with the maximum query frequency as the medical query word of each medical query object to obtain the plurality of medical query words corresponding to the plurality of medical query objects.
6. The medical prescription query method of claim 1, wherein said calculating the similarity of each query result to the plurality of medical query terms comprises:
acquiring data characteristics of each query result;
calculating the similarity of each data feature and each medical query word by using a distance formula to obtain a plurality of first similarities of each data feature;
acquiring a first similarity with the maximum similarity from the plurality of first similarities as the feature similarity of each data feature;
and performing addition operation on the feature similarity of each data feature to obtain the similarity of each query result and the plurality of medical query words.
7. The medical prescription query method of claim 1, wherein after determining the query result with the highest similarity as the target result of the medical prescription query request, the method further comprises:
acquiring a sending terminal of the medical prescription query request, and acquiring a request identifier of the medical prescription query request;
generating prompt information according to the request identification and the target result;
and sending the prompt information to the sending terminal.
8. A medical prescription inquiry apparatus, characterized by comprising:
the medical prescription query unit is used for receiving a medical prescription query request, and extracting a plurality of medical query objects from the medical prescription query request;
the determining unit is used for determining the fields of the medical query objects and determining a target database according to the fields;
the generating unit is used for generating a plurality of medical query terms according to the plurality of medical query objects;
the searching unit is used for searching the target database by using the plurality of medical query terms to obtain a plurality of query results;
the calculation unit is used for calculating the similarity between each query result and the plurality of medical query terms;
the determining unit is further configured to determine the query result with the highest similarity as the target result of the medical prescription query request.
9. An electronic device, characterized in that the electronic device comprises:
a memory storing computer readable instructions; and
a processor executing computer readable instructions stored in the memory to implement the medical prescription query method of any of claims 1 to 7.
10. A computer-readable storage medium characterized by: the computer-readable storage medium has stored therein computer-readable instructions that are executed by a processor in an electronic device to implement the medical prescription query method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010917922.4A CN111986771A (en) | 2020-09-03 | 2020-09-03 | Medical prescription query method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010917922.4A CN111986771A (en) | 2020-09-03 | 2020-09-03 | Medical prescription query method and device, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111986771A true CN111986771A (en) | 2020-11-24 |
Family
ID=73447448
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010917922.4A Pending CN111986771A (en) | 2020-09-03 | 2020-09-03 | Medical prescription query method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111986771A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113076401A (en) * | 2021-04-09 | 2021-07-06 | 北京元年科技股份有限公司 | Method for data services and corresponding system, computer device and medium |
| CN113380359A (en) * | 2021-06-01 | 2021-09-10 | 上海德衡数据科技有限公司 | Medical information query method and device based on Internet of things and electronic equipment |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108121800A (en) * | 2017-12-21 | 2018-06-05 | 北京百度网讯科技有限公司 | Information generating method and device based on artificial intelligence |
| CN109753517A (en) * | 2018-12-06 | 2019-05-14 | 北京明略软件系统有限公司 | A kind of method, apparatus, computer storage medium and the terminal of information inquiry |
| CN110765295A (en) * | 2019-09-06 | 2020-02-07 | 中国平安财产保险股份有限公司 | Graph database-based query method and device, computer equipment and storage medium |
| CN111061835A (en) * | 2019-12-17 | 2020-04-24 | 医渡云（北京）技术有限公司 | Query method and device, electronic equipment and computer readable storage medium |
| CN111291069A (en) * | 2018-12-07 | 2020-06-16 | 北京搜狗科技发展有限公司 | Data processing method and device and electronic equipment |
| CN111552767A (en) * | 2019-02-11 | 2020-08-18 | 阿里巴巴集团控股有限公司 | Search method, search device and computer equipment |
-
2020
- 2020-09-03 CN CN202010917922.4A patent/CN111986771A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108121800A (en) * | 2017-12-21 | 2018-06-05 | 北京百度网讯科技有限公司 | Information generating method and device based on artificial intelligence |
| CN109753517A (en) * | 2018-12-06 | 2019-05-14 | 北京明略软件系统有限公司 | A kind of method, apparatus, computer storage medium and the terminal of information inquiry |
| CN111291069A (en) * | 2018-12-07 | 2020-06-16 | 北京搜狗科技发展有限公司 | Data processing method and device and electronic equipment |
| CN111552767A (en) * | 2019-02-11 | 2020-08-18 | 阿里巴巴集团控股有限公司 | Search method, search device and computer equipment |
| CN110765295A (en) * | 2019-09-06 | 2020-02-07 | 中国平安财产保险股份有限公司 | Graph database-based query method and device, computer equipment and storage medium |
| CN111061835A (en) * | 2019-12-17 | 2020-04-24 | 医渡云（北京）技术有限公司 | Query method and device, electronic equipment and computer readable storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 林中燕主编: "《电子商务 智慧社会》", 上海大学出版社, pages: 162 - 163 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113076401A (en) * | 2021-04-09 | 2021-07-06 | 北京元年科技股份有限公司 | Method for data services and corresponding system, computer device and medium |
| CN113076401B (en) * | 2021-04-09 | 2022-03-04 | 北京元年科技股份有限公司 | Method for data services and corresponding system, computer device and medium |
| CN113380359A (en) * | 2021-06-01 | 2021-09-10 | 上海德衡数据科技有限公司 | Medical information query method and device based on Internet of things and electronic equipment |
| CN113380359B (en) * | 2021-06-01 | 2022-12-13 | 上海德衡数据科技有限公司 | Medical information query method and device based on Internet of things and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111985241B (en) | Medical information query method, device, electronic equipment and medium | |
| CN112199494B (en) | Medical information searching method, device, electronic equipment and storage medium | |
| CN111883251A (en) | Medical misdiagnosis detection method and device, electronic equipment and storage medium | |
| CN111538816B (en) | Question-answering method, device, electronic equipment and medium based on AI identification | |
| CN111797351A (en) | Page data management method and device, electronic equipment and medium | |
| CN111785383B (en) | Data processing method and related equipment | |
| CN111986771A (en) | Medical prescription query method and device, electronic equipment and storage medium | |
| CN114490692A (en) | Data checking method, device, equipment and storage medium | |
| CN112632098A (en) | Dynamic generation method of structured query statement and related equipment | |
| CN113268597A (en) | Text classification method, device, equipment and storage medium | |
| CN114510487B (en) | Data table merging method, device, equipment and storage medium | |
| CN112711398A (en) | Method, device and equipment for generating buried point file and storage medium | |
| CN113420545B (en) | Abstract generation method, device, equipment and storage medium | |
| CN114372060A (en) | Data storage method, device, equipment and storage medium | |
| CN113065947A (en) | Data processing method, device, equipment and storage medium | |
| CN112199483A (en) | Information input assisting method and device, electronic equipment and storage medium | |
| CN113064972A (en) | Intelligent question and answer method, device, equipment and storage medium | |
| CN112434062A (en) | Quasi-real-time data processing method, device, server and storage medium | |
| CN112819305A (en) | Service index analysis method, device, equipment and storage medium | |
| CN111933241B (en) | Medical data analysis method, device, electronic equipment and storage medium | |
| CN112395408B (en) | Stop word list generation method and device, electronic equipment and storage medium | |
| CN113282218A (en) | Multi-dimensional report generation method, device, equipment and storage medium | |
| CN114238296A (en) | Product index data display method, device, equipment and storage medium | |
| CN114692204A (en) | Data query method, device, equipment and storage medium | |
| CN112199493B (en) | Medication accuracy determining method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20220921 Address after: Room 2601 (Unit 07), Qianhai Free Trade Building, No. 3048, Xinghai Avenue, Nanshan Street, Qianhai Shenzhen-Hong Kong Cooperation Zone, Shenzhen, Guangdong 518000 Applicant after: Shenzhen Ping An Smart Healthcare Technology Co.,Ltd. Address before: 1-34 / F, Qianhai free trade building, 3048 Xinghai Avenue, Mawan, Qianhai Shenzhen Hong Kong cooperation zone, Shenzhen, Guangdong 518000 Applicant before: Ping An International Smart City Technology Co.,Ltd. |
|
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20201124 |