CN111986768B - Method and device for generating query report of clinic, electronic equipment and storage medium - Google Patents
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Abstract
The invention relates to intelligent medical treatment and provides a method, a device, electronic equipment and a storage medium for generating a query report of a clinic. The method can extract a query text from a query report generation request of a clinic, preprocesses the query text to obtain a plurality of segmentation words, screens at least one feature word from the plurality of segmentation words based on preset clinic features, the clinic features comprise clinic organization names, inputs the at least one feature word into a pre-constructed query model to obtain at least one output result, acquires at least one query report corresponding to the at least one output result from a clinic system, and integrates the at least one query report to obtain the clinic report. The clinic report generated by the invention is convenient for analysis and statistics, and can accurately acquire the query requirement of the user on the premise of not limiting the input mode of the user. Furthermore, the present invention relates to blockchain technology, where the clinic report may be stored.
Description
Technical Field
The invention relates to the technical field of intelligent medical treatment, in particular to a method and a device for generating a query report of a clinic, electronic equipment and a storage medium.
Background
At present, various different types of data are generated in the running process of a clinic, and different types of data reports such as qualification supervision reports, provider record statistics and the like can be formed through the data. When a user needs to acquire report data with multiple requirements, the user is required to input the requirements according to a certain input mode, and relevant query operation is executed in a clinic system according to page guiding operation.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a method, an apparatus, an electronic device, and a storage medium for generating a query report of a clinic, which not only can integrate data corresponding to a plurality of dimensions into the query report of the same clinic, thereby facilitating analysis and statistics of the data, but also can accurately obtain the query requirement of a user without limiting the input mode of the user.
In one aspect, the present invention provides a method for generating a query report of a clinic, where the method includes:
Extracting query text from a clinic query report generation request when the clinic query report generation request is received;
preprocessing the query text to obtain a plurality of segmentation words;
screening at least one feature word from the plurality of segmentation words based on preset clinic features, wherein the clinic features comprise clinic organization names;
inputting the at least one feature word into a pre-constructed query model to obtain at least one output result;
obtaining at least one query report corresponding to the at least one output result from the clinic system;
and integrating the at least one query report to obtain a clinic report.
According to a preferred embodiment of the present invention, said extracting query text from said clinic query report generating request comprises:
acquiring idle threads in a preset thread pool;
analyzing the report generation request message of the clinic inquiry report by using the idle thread to obtain the data information carried by the report generation request of the clinic inquiry;
acquiring a preset label, wherein the preset label is a predefined label;
and acquiring information corresponding to the preset label from the data information to serve as the query text.
According to a preferred embodiment of the present invention, the preprocessing the query text to obtain a plurality of word segments includes:
segmenting the query text according to a preset custom dictionary to obtain segmentation positions, wherein a plurality of custom words and weights corresponding to each custom word are stored in the custom dictionary;
constructing at least one directed acyclic graph according to the segmentation position;
calculating the segmentation probability of each directed acyclic graph according to the weight value in the custom dictionary;
determining a segmentation position corresponding to the directed acyclic graph with the maximum segmentation probability as a target segmentation position;
dividing the query text according to the target dividing position to obtain divided words;
identifying useless labels in the segmented words, and filtering the useless labels from the segmented words to obtain a plurality of target words;
and carrying out standardization processing on the target words to obtain the word segmentation words.
According to a preferred embodiment of the present invention, the screening at least one feature word from the plurality of word segments based on the preset clinic feature includes:
performing coding processing on each word segment to obtain a plurality of coding vectors corresponding to the plurality of word segments, and obtaining a plurality of feature vectors corresponding to the clinic features;
Calculating the distance between each coding vector and each characteristic vector to obtain a plurality of characteristic distances of each coding vector;
selecting a feature distance with the minimum value from a plurality of feature distances of each code vector as a target distance of each code vector;
and screening the code vector with the target distance smaller than a preset threshold value as a target code vector, and determining the segmentation corresponding to the target code vector as the at least one feature word.
According to a preferred embodiment of the present invention, before inputting the at least one feature word into the pre-constructed query model to obtain at least one output result, the method further includes:
acquiring historical clinic query data from a clinic query corpus, wherein the clinic query corpus stores a plurality of clinic query data and a plurality of query categories;
dividing the historical clinic query data to obtain a training clinic data set and a verification clinic data set;
training historical clinic query data in the training clinic data set to obtain a first learner;
adjusting the first learner according to historical clinic query data in the verification clinic data set to obtain a second learner;
Acquiring target clinic query data with query time within configuration time from the clinic query corpus;
performing error analysis on the second learner by utilizing the target clinic query data to obtain an error rate;
determining the second learner as the query model when the error rate is less than a configuration value; or alternatively
And when the error rate is greater than or equal to the configuration value, utilizing the query data of the target clinic to adjust the second learner until the error rate is less than the configuration value, and obtaining the query model.
In accordance with a preferred embodiment of the present invention, prior to obtaining historical office query data from the office query corpus, the method further comprises:
calculating the quantity of clinic query data of each query category in the clinic query corpus;
judging whether the number is smaller than a preset number threshold value or not;
and when the quantity is smaller than the preset quantity threshold value, increasing the quantity of the clinic query data of the query category corresponding to the quantity through a perturbation method.
According to a preferred embodiment of the invention, after having been reported by the clinic, the method further comprises:
encrypting the clinic report by adopting a symmetrical encryption technology to obtain a ciphertext;
Determining a triggering user of the clinic query report generation request;
and sending the ciphertext to the terminal equipment of the triggering user.
On the other hand, the invention also provides a device for generating the inquiry report of the clinic, which comprises the following components:
an extraction unit for extracting a query text from an office query report generation request when the office query report generation request is received;
the preprocessing unit is used for preprocessing the query text to obtain a plurality of segmentation words;
the screening unit is used for screening at least one characteristic word from the plurality of segmented words based on preset clinic characteristics, wherein the clinic characteristics comprise clinic organization names;
the input unit is used for inputting the at least one characteristic word into a pre-constructed query model to obtain at least one output result;
an acquisition unit for acquiring at least one query report corresponding to the at least one output result from the clinic system;
and the integrating unit is used for integrating the at least one inquiry report to obtain a clinic report.
In another aspect, the present invention also proposes an electronic device, including:
a memory storing computer readable instructions; and
A processor executing computer readable instructions stored in the memory to implement the clinic query report generating method.
In another aspect, the present invention also provides a computer-readable storage medium having stored therein computer-readable instructions executable by a processor in an electronic device to implement the method for generating a query report for a clinic.
According to the technical scheme, when the query report generation request of the clinic is received, the query text can be extracted from the query report generation request of the clinic, the query text can be accurately acquired, the query text is preprocessed to obtain a plurality of segmentation words, useless labels in the query text can be cleaned out through preprocessing the query text, analysis efficiency of the query text is improved, in addition, unification of labels can be realized, screening of subsequent feature words is facilitated, at least one feature word is screened out from the plurality of segmentation words based on preset clinic features, the clinic features comprise clinic organization names, the feature words can be rapidly screened out through the preset clinic features, screening efficiency is improved, the at least one feature word is input into a pre-built query model, at least one output result is obtained, the query of a user can be accurately identified through the query model, at least one query report corresponding to the at least one output result is obtained from a clinic system, the at least one query word is integrated, the at least one query report is obtained, and the query report corresponding to the intention of the user is integrated, and the intention of the user is convenient to report. The invention not only can integrate the data corresponding to a plurality of dimensions into the query report of the same clinic, is beneficial to the analysis and statistics of the data, but also can accurately acquire the query requirement of the user on the premise of not limiting the input mode of the user. The method is also applied to the intelligent medical scene, so that the construction of the intelligent city is promoted.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of the method of generating a query report in a clinic of the present invention.
FIG. 2 is a functional block diagram of a preferred embodiment of the query report generating device of the present invention.
FIG. 3 is a schematic diagram of an electronic device implementing a preferred embodiment of the method for generating a query report for a clinic according to the present 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.
As shown in FIG. 1, a flow chart of a preferred embodiment of the method for generating a query report in a clinic of the present invention is shown. The order of the steps in the flowchart may be changed and some steps may be omitted according to various needs.
The clinic query report generation method is applied to the intelligent medical scene, so that the construction of the intelligent city is promoted. The method is applied to one or more electronic devices, wherein the electronic devices are devices capable of automatically performing numerical calculation and/or information processing according to preset or stored computer readable instructions, and the hardware comprises, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (Field-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices and the like.
The electronic device may be any electronic product that can interact with a user in a human-computer manner, such as a personal computer, tablet computer, smart phone, personal digital assistant (Personal Digital Assistant, PDA), game console, interactive internet protocol television (Internet Protocol Television, IPTV), smart wearable device, etc.
The electronic device may comprise a network device and/or a user device. Wherein the network device includes, but is not limited to, a single network electronic device, a group of electronic devices made up of multiple network electronic devices, or a Cloud based Cloud Computing (Cloud Computing) made up of a large number of hosts or network electronic devices.
The network on which the electronic device is located includes, but is not limited to: the internet, wide area networks, metropolitan area networks, local area networks, virtual private networks (Virtual Private Network, VPN), etc.
S10, when receiving a clinic query report generation request, extracting query text from the clinic query report generation request.
In at least one embodiment of the invention, the clinic query report generation request may be triggered by a supervisor.
In at least one embodiment of the present invention, the data information carried by the clinic query report generation request includes, but is not limited to: the query text.
The query text can be manually input by the supervisory personnel according to own requirements, or can be obtained by voice conversion input by the supervisory personnel. For example, the query text may be a qualification report of the clinic for the last year and the number of uses of the antimicrobial prescription.
In at least one embodiment of the invention, the electronic device extracting query text from the clinic query report generation request comprises:
acquiring idle threads in a preset thread pool;
analyzing the report generation request message of the clinic inquiry report by using the idle thread to obtain the data information carried by the report generation request of the clinic inquiry;
acquiring a preset label, wherein the preset label is a predefined label;
and acquiring information corresponding to the preset label from the data information to serve as the query text.
For example, the preset tag may be a name.
The message of the query report generation request of the clinic is analyzed through the idle thread, and the idle thread is not required to wait for processing other requests and analyzing the whole query report generation request of the clinic, so that the analysis efficiency of the query report generation request of the clinic can be improved, and in addition, the query text can be accurately acquired through the mapping relation between the preset label and the query text.
S11, preprocessing the query text to obtain a plurality of segmentation words.
In at least one embodiment of the present invention, the preprocessing operation includes: word segmentation, useless label cleaning and standardization processing.
In at least one embodiment of the present invention, the electronic device pre-processes the query text to obtain a plurality of terms, including:
segmenting the query text according to a preset custom dictionary to obtain segmentation positions, wherein a plurality of custom words and weights corresponding to each custom word are stored in the custom dictionary;
constructing at least one directed acyclic graph according to the segmentation position;
calculating the segmentation probability of each directed acyclic graph according to the weight value in the custom dictionary;
determining a segmentation position corresponding to the directed acyclic graph with the maximum segmentation probability as a target segmentation position;
dividing the query text according to the target dividing position to obtain divided words;
identifying useless labels in the segmented words, and filtering the useless labels from the segmented words to obtain a plurality of target words;
and carrying out standardization processing on the target words to obtain the word segmentation words.
Wherein, the plurality of custom words may include, but are not limited to: office institution name, time of day, report presentation, etc. For example: the differentiation time may be approximately one month.
Further, the useless tag includes: the language Qi assists words, quantity conditions and the like.
The query text is cut through the custom dictionary, the query text can be cut according to the requirements, useless labels are filtered, analysis efficiency of the query text can be improved, standardized processing is carried out on a plurality of target words, unification of the labels can be achieved, and screening of subsequent feature words is facilitated.
Specifically, the electronic device performs standardization processing on the target words, and the obtaining the word segments includes:
identifying the target words by adopting a shallow semantic analysis method;
and carrying out normalization processing on the target words with similar identified meanings to obtain the plurality of segmentation words.
S12, screening at least one feature word from the plurality of segmentation words based on preset clinic features, wherein the clinic features comprise clinic organization names.
In at least one embodiment of the invention, the predetermined clinic characteristics include clinic name, institution qualification supervision, vendor proposal statistics, antimicrobial prescription quantity, display form, and the like.
In at least one embodiment of the present invention, the electronic device, based on a preset clinic feature, selecting at least one feature word from the plurality of word segments includes:
performing coding processing on each word segment to obtain a plurality of coding vectors corresponding to the plurality of word segments, and obtaining a plurality of feature vectors corresponding to the clinic features;
calculating the distance between each coding vector and each characteristic vector to obtain a plurality of characteristic distances of each coding vector;
selecting a feature distance with the minimum value from a plurality of feature distances of each code vector as a target distance of each code vector;
and screening the code vector with the target distance smaller than a preset threshold value as a target code vector, and determining the segmentation corresponding to the target code vector as the at least one feature word.
The value of the preset threshold value can be set in a self-defined manner according to an application scene, which is not limited by the invention.
The at least one feature word can be rapidly screened out through preset clinic features, and screening efficiency is improved.
S13, inputting the at least one feature word into a pre-constructed query model to obtain at least one output result.
In at least one embodiment of the present invention, the electronic device generates a learner after pre-training according to historical clinic query data, and performs supervised fine tuning on the learner by using a learning rate to obtain the query model.
In at least one embodiment of the present invention, the at least one output result may be a result obtained after the at least one feature word is input to the query model, and the at least one output result generally includes, but is not limited to: medical institution qualification registration, trend graphs of abnormal number of on-duty doctors in the present year, distribution of intravenous infusion violations and the like.
In at least one embodiment of the present invention, before inputting the at least one feature word into the pre-constructed query model to obtain at least one output result, the method further includes:
acquiring historical clinic query data from a clinic query corpus, wherein the clinic query corpus stores a plurality of clinic query data and a plurality of query categories;
dividing the historical clinic query data to obtain a training clinic data set and a verification clinic data set;
training historical clinic query data in the training clinic data set to obtain a first learner;
Adjusting the first learner according to historical clinic query data in the verification clinic data set to obtain a second learner;
acquiring target clinic query data with query time within configuration time from the clinic query corpus;
performing error analysis on the second learner by utilizing the target clinic query data to obtain an error rate;
determining the second learner as the query model when the error rate is less than a configuration value; or alternatively
And when the error rate is greater than or equal to the configuration value, utilizing the query data of the target clinic to adjust the second learner until the error rate is less than the configuration value, and obtaining the query model.
The clinic query corpus stores a plurality of clinic query data, query time of each clinic query data, query personnel of each clinic query data and the like.
Further, the configuration time may be set arbitrarily according to the requirement, for example: last two days, last week, etc.
Still further, the configuration values may be determined based on the accuracy of the requirements for the query model, for example: the required accuracy for the query model is 95% and the error rate is 5%.
Through the embodiment, the first learner can be rapidly determined, and then the fitting degree of the second learner can be improved according to the historical clinic query data in the verification clinic data set, and then the accuracy of the query model can be ensured by utilizing the target clinic query data of the query time within the configuration time.
In at least one embodiment of the invention, prior to obtaining historical office query data from the office query corpus, the method further comprises:
calculating the quantity of clinic query data of each query category in the clinic query corpus;
judging whether the number is smaller than a preset number threshold value or not;
and when the quantity is smaller than the preset quantity threshold value, increasing the quantity of the clinic query data of the query category corresponding to the quantity through a perturbation method.
Wherein the query categories include: time category, area category, presentation category, etc.
When the number of the clinic query data of a certain query class is smaller than a preset number threshold, the electronic equipment adopts a disturbance method to disturbance the clinic query data of the query class so as to increase the number of the query class, and the problem that the generalization capability of a trained query model on the data of the query class is poor due to the insufficient number of samples of the query class is avoided. The disturbance method is the prior art, and the present invention is not described herein.
In at least one embodiment of the present invention, the electronic device inputs the at least one feature word into a pre-constructed query model, and can accurately identify the query intention of the supervisor through the query model.
S14, at least one query report corresponding to the at least one output result is obtained from the clinic system.
In at least one embodiment of the invention, the clinic system stores data reports for a plurality of clinic facilities.
In at least one embodiment of the present invention, the electronic device obtaining at least one query report corresponding to the at least one output result from the clinic system comprises:
determining an output number of the at least one output result;
and based on the at least one output result, invoking processing threads with the output number to query in the clinic system to obtain the at least one query report.
By the embodiment, the at least one query report can be quickly acquired.
S15, integrating the at least one inquiry report to obtain a clinic report.
It is emphasized that to further ensure privacy and security of the clinic report, the clinic report may also be stored in a blockchain node.
In at least one embodiment of the invention, the clinic report is aggregated with the at least one query report.
In at least one embodiment of the invention, after reporting to the clinic, the method further comprises:
encrypting the clinic report by adopting a symmetrical encryption technology to obtain a ciphertext;
determining a triggering user of the clinic query report generation request;
and sending the ciphertext to the terminal equipment of the triggering user.
By encrypting the clinic report, the security of the clinic report can be improved, and furthermore, by determining the trigger user, the clinic report can be accurately transmitted to the trigger user.
According to the technical scheme, when the query report generation request of the clinic is received, the query text can be extracted from the query report generation request of the clinic, the query text can be accurately acquired, the query text is preprocessed to obtain a plurality of segmentation words, useless labels in the query text can be cleaned out through preprocessing the query text, analysis efficiency of the query text is improved, in addition, unification of labels can be realized, screening of subsequent feature words is facilitated, at least one feature word is screened out from the plurality of segmentation words based on preset clinic features, the clinic features comprise clinic organization names, the feature words can be rapidly screened out through the preset clinic features, screening efficiency is improved, the at least one feature word is input into a pre-built query model, at least one output result is obtained, the query of a user can be accurately identified through the query model, at least one query report corresponding to the at least one output result is obtained from a clinic system, the at least one query word is integrated, the at least one query report is obtained, and the query report corresponding to the intention of the user is integrated, and the intention of the user is convenient to report. The invention not only can integrate the data corresponding to a plurality of dimensions into the query report of the same clinic, is beneficial to the analysis and statistics of the data, but also can accurately acquire the query requirement of the user on the premise of not limiting the input mode of the user. The method is also applied to the intelligent medical scene, so that the construction of the intelligent city is promoted.
FIG. 2 is a functional block diagram of a preferred embodiment of the query report generating device of the present invention. The clinic inquiry report generating device 11 includes an extracting unit 110, a preprocessing unit 111, a screening unit 112, an input unit 113, an obtaining unit 114, an integrating unit 115, a dividing unit 116, a training unit 117, an adjusting unit 118, an analyzing unit 119, a determining unit 120, a calculating unit 121, a judging unit 122, an encrypting unit 123, and a transmitting unit 124. The module/unit referred to herein is a series of computer readable instructions capable of being retrieved by the processor 13 and performing a fixed function and stored in the memory 12. In the present embodiment, the functions of the respective modules/units will be described in detail in the following embodiments.
When receiving the clinic query report generating request, the extracting unit 110 extracts query text from the clinic query report generating request.
In at least one embodiment of the invention, the clinic query report generation request may be triggered by a supervisor.
In at least one embodiment of the present invention, the data information carried by the clinic query report generation request includes, but is not limited to: the query text.
The query text can be manually input by the supervisory personnel according to own requirements, or can be obtained by voice conversion input by the supervisory personnel. For example, the query text may be a qualification report of the clinic for the last year and the number of uses of the antimicrobial prescription.
In at least one embodiment of the present invention, the extracting unit 110 extracting query text from the clinic query report generating request includes:
acquiring idle threads in a preset thread pool;
analyzing the report generation request message of the clinic inquiry report by using the idle thread to obtain the data information carried by the report generation request of the clinic inquiry;
acquiring a preset label, wherein the preset label is a predefined label;
and acquiring information corresponding to the preset label from the data information to serve as the query text.
For example, the preset tag may be a name.
The message of the query report generation request of the clinic is analyzed through the idle thread, and the idle thread is not required to wait for processing other requests and analyzing the whole query report generation request of the clinic, so that the analysis efficiency of the query report generation request of the clinic can be improved, and in addition, the query text can be accurately acquired through the mapping relation between the preset label and the query text.
The preprocessing unit 111 performs preprocessing on the query text to obtain a plurality of segmentation words.
In at least one embodiment of the present invention, the preprocessing operation includes: word segmentation, useless label cleaning and standardization processing.
In at least one embodiment of the present invention, the preprocessing unit 111 performs preprocessing on the query text to obtain a plurality of word segments, where the preprocessing includes:
segmenting the query text according to a preset custom dictionary to obtain segmentation positions, wherein a plurality of custom words and weights corresponding to each custom word are stored in the custom dictionary;
constructing at least one directed acyclic graph according to the segmentation position;
calculating the segmentation probability of each directed acyclic graph according to the weight value in the custom dictionary;
determining a segmentation position corresponding to the directed acyclic graph with the maximum segmentation probability as a target segmentation position;
dividing the query text according to the target dividing position to obtain divided words;
identifying useless labels in the segmented words, and filtering the useless labels from the segmented words to obtain a plurality of target words;
and carrying out standardization processing on the target words to obtain the word segmentation words.
Wherein, the plurality of custom words may include, but are not limited to: office institution name, time of day, report presentation, etc. For example: the differentiation time may be approximately one month.
Further, the useless tag includes: the language Qi assists words, quantity conditions and the like.
The query text is cut through the custom dictionary, the query text can be cut according to the requirements, useless labels are filtered, analysis efficiency of the query text can be improved, standardized processing is carried out on a plurality of target words, unification of the labels can be achieved, and screening of subsequent feature words is facilitated.
Specifically, the preprocessing unit 111 performs normalization processing on the target words, and the obtaining the segmented words includes:
identifying the target words by adopting a shallow semantic analysis method;
and carrying out normalization processing on the target words with similar identified meanings to obtain the plurality of segmentation words.
The screening unit 112 screens at least one feature word from the plurality of segmentation words based on preset clinic features including clinic organization names.
In at least one embodiment of the invention, the predetermined clinic characteristics include clinic name, institution qualification supervision, vendor proposal statistics, antimicrobial prescription quantity, display form, and the like.
In at least one embodiment of the present invention, the screening unit 112 screens at least one feature word from the plurality of word segments based on a preset clinic feature, including:
performing coding processing on each word segment to obtain a plurality of coding vectors corresponding to the plurality of word segments, and obtaining a plurality of feature vectors corresponding to the clinic features;
calculating the distance between each coding vector and each characteristic vector to obtain a plurality of characteristic distances of each coding vector;
selecting a feature distance with the minimum value from a plurality of feature distances of each code vector as a target distance of each code vector;
and screening the code vector with the target distance smaller than a preset threshold value as a target code vector, and determining the segmentation corresponding to the target code vector as the at least one feature word.
The value of the preset threshold value can be set in a self-defined manner according to an application scene, which is not limited by the invention.
The at least one feature word can be rapidly screened out through preset clinic features, and screening efficiency is improved.
The input unit 113 inputs the at least one feature word into a pre-constructed query model, and obtains at least one output result.
In at least one embodiment of the present invention, a learner is generated after pre-training according to historical clinic query data, and supervised fine tuning is performed on the learner by using a learning rate to obtain the query model.
In at least one embodiment of the present invention, the at least one output result may be a result obtained after the at least one feature word is input to the query model, and the at least one output result generally includes, but is not limited to: medical institution qualification registration, trend graphs of abnormal number of on-duty doctors in the present year, distribution of intravenous infusion violations and the like.
In at least one embodiment of the present invention, before inputting the at least one feature word into a pre-constructed query model to obtain at least one output result, the obtaining unit 114 obtains historical clinic query data from a clinic query corpus, where a plurality of clinic query data and a plurality of query categories are stored;
the dividing unit 116 divides the historical clinic query data to obtain a training clinic data set and a verification clinic data set;
The adjusting unit 118 adjusts the first learner according to the historical clinic query data in the verification clinic data set to obtain a second learner;
the obtaining unit 114 obtains target clinic query data with query time within configuration time from the clinic query corpus;
the analysis unit 119 performs error analysis on the second learner by using the target clinic query data to obtain an error rate;
when the error rate is smaller than a configuration value, the determination unit 120 determines the second learner as the query model; or alternatively
When the error rate is greater than or equal to the configuration value, the adjustment unit 118 adjusts the second learner using the query data of the target clinic until the error rate is less than the configuration value, to obtain the query model.
The clinic query corpus stores a plurality of clinic query data, query time of each clinic query data, query personnel of each clinic query data and the like.
Further, the configuration time may be set arbitrarily according to the requirement, for example: last two days, last week, etc.
Still further, the configuration values may be determined based on the accuracy of the requirements for the query model, for example: the required accuracy for the query model is 95% and the error rate is 5%.
Through the embodiment, the first learner can be rapidly determined, and then the fitting degree of the second learner can be improved according to the historical clinic query data in the verification clinic data set, and then the accuracy of the query model can be ensured by utilizing the target clinic query data of the query time within the configuration time.
In at least one embodiment of the present invention, the calculation unit 121 calculates the number of clinic query data for each query category in the clinic query corpus before acquiring historical clinic query data from the clinic query corpus;
the judgment unit 122 judges whether the number is smaller than a preset number threshold;
when the number is smaller than the preset number threshold, the calculation unit 121 increases the number of pieces of clinic query data of the query class corresponding to the number by a perturbation method.
Wherein the query categories include: time category, area category, presentation category, etc.
When the number of the office query data of a certain query class is smaller than the preset number threshold, the computing unit 121 uses a perturbation method to perturb the office query data of the query class, so as to increase the number of the query classes, and avoid poor generalization capability of the trained query model on the data of the query class due to insufficient sample number of the query class. The disturbance method is the prior art, and the present invention is not described herein.
In at least one embodiment of the present invention, the input unit 113 inputs the at least one feature word into a previously constructed query model, by which the query intention of the supervisor can be accurately recognized.
The obtaining unit 114 obtains at least one query report corresponding to the at least one output result from the clinic system.
In at least one embodiment of the invention, the clinic system stores data reports for a plurality of clinic facilities.
In at least one embodiment of the present invention, the obtaining unit 114 obtains at least one query report corresponding to the at least one output result from the clinic system, including:
determining an output number of the at least one output result;
and based on the at least one output result, invoking processing threads with the output number to query in the clinic system to obtain the at least one query report.
By the embodiment, the at least one query report can be quickly acquired.
The integration unit 115 integrates the at least one query report to obtain a clinic report.
It is emphasized that to further ensure privacy and security of the clinic report, the clinic report may also be stored in a blockchain node.
In at least one embodiment of the invention, the clinic report is aggregated with the at least one query report.
In at least one embodiment of the present invention, after obtaining the clinic report, the encryption unit 123 encrypts the clinic report using a symmetric encryption technique to obtain ciphertext;
the determining unit 120 determines a triggering user of the clinic query report generating request;
the sending unit 124 sends the ciphertext to the terminal device of the triggering user.
By encrypting the clinic report, the security of the clinic report can be improved, and furthermore, by determining the trigger user, the clinic report can be accurately transmitted to the trigger user.
According to the technical scheme, when the query report generation request of the clinic is received, the query text can be extracted from the query report generation request of the clinic, the query text can be accurately acquired, the query text is preprocessed to obtain a plurality of segmentation words, useless labels in the query text can be cleaned out through preprocessing the query text, analysis efficiency of the query text is improved, in addition, unification of labels can be realized, screening of subsequent feature words is facilitated, at least one feature word is screened out from the plurality of segmentation words based on preset clinic features, the clinic features comprise clinic organization names, the feature words can be rapidly screened out through the preset clinic features, screening efficiency is improved, the at least one feature word is input into a pre-built query model, at least one output result is obtained, the query of a user can be accurately identified through the query model, at least one query report corresponding to the at least one output result is obtained from a clinic system, the at least one query word is integrated, the at least one query report is obtained, and the query report corresponding to the intention of the user is integrated, and the intention of the user is convenient to report. The invention not only can integrate the data corresponding to a plurality of dimensions into the query report of the same clinic, is beneficial to the analysis and statistics of the data, but also can accurately acquire the query requirement of the user on the premise of not limiting the input mode of the user. The method is also applied to the intelligent medical scene, so that the construction of the intelligent city is promoted.
Fig. 3 is a schematic structural diagram of an electronic device according to a preferred embodiment of the present invention for implementing the method for generating a query report in a clinic.
In one embodiment of the invention, the electronic device 1 includes, but is not limited to, a memory 12, a processor 13, and computer readable instructions stored in the memory 12 and executable on the processor 13, such as a clinic query report generating program.
It will be appreciated by those skilled in the art that the schematic diagram is merely an example of the electronic device 1 and does not constitute a limitation of the electronic device 1, and may include more or less components than illustrated, or may combine certain components, or different components, e.g. the electronic device 1 may further include input-output devices, network access devices, buses, etc.
The processor 13 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor, etc., and the processor 13 is an operation core and a control center of the electronic device 1, connects various parts of the entire electronic device 1 using various interfaces and lines, and executes an operating system of the electronic device 1 and various installed applications, program codes, etc.
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 complete the present invention. The one or more modules/units may be a series of computer readable instructions capable of performing a specific function, the computer readable instructions describing a process of executing the computer readable instructions in the electronic device 1. For example, the computer-readable instructions may be divided into an extraction unit 110, a preprocessing unit 111, a screening unit 112, an input unit 113, an acquisition unit 114, an integration unit 115, a division unit 116, a training unit 117, an adjustment unit 118, an analysis unit 119, a determination unit 120, a calculation unit 121, a judgment unit 122, an encryption unit 123, and a transmission unit 124.
The memory 12 may be used to store the computer readable instructions and/or modules, and the processor 13 may implement 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 storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data created according to the use of the electronic device, etc. Memory 12 may include non-volatile and volatile memory, such as: a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, 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 physical memory, such as a memory bank, 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 implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the present invention may also be implemented by implementing all or part of the processes in the methods of the embodiments described above, by instructing the associated hardware by means of computer readable instructions, which may be stored in a computer readable storage medium, the computer readable instructions, when executed by a processor, implementing the steps of the respective method embodiments described above.
Wherein the computer readable instructions comprise computer readable instruction code which may be in the form of source code, object code, executable files, or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer readable instruction code, a recording medium, a USB flash disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory).
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
In connection with fig. 1, the memory 12 in the electronic device 1 stores computer readable instructions implementing a method for generating a query report for a clinic, the processor 13 being executable to implement:
extracting query text from a clinic query report generation request when the clinic query report generation request is received;
preprocessing the query text to obtain a plurality of segmentation words;
screening at least one feature word from the plurality of segmentation words based on preset clinic features, wherein the clinic features comprise clinic organization names;
inputting the at least one feature word into a pre-constructed query model to obtain at least one output result;
Obtaining at least one query report corresponding to the at least one output result from the clinic system;
and integrating the at least one query report to obtain a clinic report.
In particular, the specific implementation method of the processor 13 on the computer readable instructions may refer to the description of the relevant steps in the corresponding embodiment of fig. 1, which is not repeated herein.
In the several embodiments provided in the present invention, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The computer readable storage medium has stored thereon computer readable instructions, wherein the computer readable instructions when executed by the processor 13 are configured to implement the steps of:
extracting query text from a clinic query report generation request when the clinic query report generation request is received;
preprocessing the query text to obtain a plurality of segmentation words;
screening at least one feature word from the plurality of segmentation words based on preset clinic features, wherein the clinic features comprise clinic organization names;
Inputting the at least one feature word into a pre-constructed query model to obtain at least one output result;
obtaining at least one query report corresponding to the at least one output result from the clinic system;
and integrating the at least one query report to obtain a clinic report.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
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 evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (9)
1. A method of generating a clinic query report, the method comprising:
extracting query text from a clinic query report generation request when the clinic query report generation request is received;
preprocessing the query text to obtain a plurality of segmentation words;
screening at least one feature word from the plurality of segmentation words based on preset clinic features, wherein the step of screening at least one feature word comprises the following steps: performing coding processing on each word segment to obtain a plurality of coding vectors corresponding to the plurality of word segments, and obtaining a plurality of feature vectors corresponding to the clinic features; calculating the distance between each coding vector and each characteristic vector to obtain a plurality of characteristic distances of each coding vector; selecting a feature distance with the minimum value from a plurality of feature distances of each code vector as a target distance of each code vector; screening the code vector with the target distance smaller than a preset threshold value as a target code vector, and determining the segmentation corresponding to the target code vector as the at least one feature word, wherein the clinic feature comprises a clinic organization name;
Inputting the at least one feature word into a pre-constructed query model to obtain at least one output result, wherein the query model is generated by performing supervised fine tuning on a learner by using a learning rate, and the learner is generated by performing pre-training according to historical clinic query data;
obtaining at least one query report corresponding to the at least one output result from the clinic system;
and integrating the at least one query report to obtain a clinic report.
2. The method of claim 1, wherein extracting query text from the clinic query report generation request comprises:
acquiring idle threads in a preset thread pool;
analyzing the report generation request message of the clinic inquiry report by using the idle thread to obtain the data information carried by the report generation request of the clinic inquiry;
acquiring a preset label, wherein the preset label is a predefined label;
and acquiring information corresponding to the preset label from the data information to serve as the query text.
3. The method for generating a query report in a clinic of claim 1, wherein preprocessing the query text to obtain a plurality of segmentation words comprises:
Segmenting the query text according to a preset custom dictionary to obtain segmentation positions, wherein a plurality of custom words and weights corresponding to each custom word are stored in the custom dictionary;
constructing at least one directed acyclic graph according to the segmentation position;
calculating the segmentation probability of each directed acyclic graph according to the weight value in the custom dictionary;
determining a segmentation position corresponding to the directed acyclic graph with the maximum segmentation probability as a target segmentation position;
dividing the query text according to the target dividing position to obtain divided words;
identifying useless labels in the segmented words, and filtering the useless labels from the segmented words to obtain a plurality of target words;
and carrying out standardization processing on the target words to obtain the word segmentation words.
4. The method of generating a query report in a clinic of claim 1, wherein prior to inputting the at least one feature word into a pre-built query model to obtain at least one output result, the method further comprises:
acquiring the historical clinic query data from a clinic query corpus, wherein the clinic query corpus stores a plurality of clinic query data and a plurality of query categories;
Dividing the historical clinic query data to obtain a training clinic data set and a verification clinic data set;
training historical clinic query data in the training clinic data set to obtain a first learner;
adjusting the first learner according to historical clinic query data in the verification clinic data set to obtain a second learner;
acquiring target clinic query data with query time within configuration time from the clinic query corpus;
performing error analysis on the second learner by utilizing the target clinic query data to obtain an error rate;
determining the second learner as the query model when the error rate is less than a configuration value; or alternatively
And when the error rate is greater than or equal to the configuration value, utilizing the query data of the target clinic to adjust the second learner until the error rate is less than the configuration value, and obtaining the query model.
5. The clinic query report generating method according to claim 4, wherein prior to obtaining the historical clinic query data from a clinic query corpus, the method further comprises:
calculating the quantity of clinic query data of each query category in the clinic query corpus;
Judging whether the number is smaller than a preset number threshold value or not;
and when the quantity is smaller than the preset quantity threshold value, increasing the quantity of the clinic query data of the query category corresponding to the quantity through a perturbation method.
6. The clinic query report generating method according to claim 1, wherein after obtaining the clinic report, the method further comprises:
encrypting the clinic report by adopting a symmetrical encryption technology to obtain a ciphertext;
determining a triggering user of the clinic query report generation request;
and sending the ciphertext to the terminal equipment of the triggering user.
7. An office query report generating device, the office query report generating device comprising:
an extraction unit for extracting a query text from an office query report generation request when the office query report generation request is received;
the preprocessing unit is used for preprocessing the query text to obtain a plurality of segmentation words;
the screening unit is used for screening at least one feature word from the plurality of segmentation words based on preset clinic features, and comprises the following steps: performing coding processing on each word segment to obtain a plurality of coding vectors corresponding to the plurality of word segments, and obtaining a plurality of feature vectors corresponding to the clinic features; calculating the distance between each coding vector and each characteristic vector to obtain a plurality of characteristic distances of each coding vector; selecting a feature distance with the minimum value from a plurality of feature distances of each code vector as a target distance of each code vector; screening the code vector with the target distance smaller than a preset threshold value as a target code vector, and determining the segmentation corresponding to the target code vector as the at least one feature word, wherein the clinic feature comprises a clinic organization name;
The input unit is used for inputting the at least one characteristic word into a pre-constructed query model to obtain at least one output result, the query model is generated by performing supervised fine tuning on a learner by using a learning rate, and the learner is generated by performing pre-training according to historical clinic query data;
an acquisition unit for acquiring at least one query report corresponding to the at least one output result from the clinic system;
and the integrating unit is used for integrating the at least one inquiry report to obtain a clinic report.
8. An electronic device, the electronic device comprising:
a memory storing computer readable instructions; and
A processor executing computer readable instructions stored in the memory to implement the clinic query report generating method of any one of claims 1 to 6.
9. A computer-readable storage medium, characterized by: the computer-readable storage medium having stored therein computer-readable instructions executable by a processor in an electronic device to implement the clinic query report generating method according to any one of claims 1 to 6.
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