CN112395883A - Inquiry processing method, inquiry data processing method and device - Google Patents
Inquiry processing method, inquiry data processing method and device Download PDFInfo
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Abstract
The application provides an inquiry processing method, an inquiry data processing method and a device, wherein the method comprises the following steps: receiving disease description data to be displayed; displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data; acquiring operation behavior data of a user on a target object; and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition. By means of the scheme, the problem that key information cannot be determined quickly and efficiently by doctor nodes in the existing short-time online inquiry process is solved, the effect of quickly and efficiently reading the key information is achieved, and inquiry efficiency is improved.
Description
Technical Field
The application belongs to the technical field of internet, and particularly relates to an inquiry processing method, an inquiry data processing method and an inquiry data processing device.
Background
In many scenarios, there is a reading requirement for large text, such as: in the image-text inquiry platform, a patient or a user generally provides image-text information of the physical condition of the patient, and then a doctor in an internet hospital (i.e., a doctor interfacing with the image-text inquiry platform) reads the image-text information provided by the user and determines the illness state of the user according to the read information.
In the existing image-text inquiry platform, after a patient inputs image-text information for explaining the state of an illness, the image-text information is generally displayed in a unified display mode at a doctor end, namely, all the image-text information is not distinguished and emphasized and is displayed in the same mode, so that the doctor can only read all the state of the illness information input by the user when reading the state of the illness of the patient, and can give reasonable judgment on the state of the illness, and the efficiency of seeing a doctor by the doctor is certainly influenced.
In consideration of the fact that if the relatively important contents in the patient's condition description input by the patient, namely the contents contributing to the patient's condition judgment, are displayed in a guiding manner, the important contents contributing to the patient's condition judgment in the patient's condition description can be quickly determined by the doctor when the patient's condition description is read, so that the doctor's diagnosis efficiency can be improved.
Disclosure of Invention
The application aims to provide an inquiry processing method, an inquiry data processing method and an inquiry data processing device, and the technical effect of effectively improving the efficiency of reading information can be achieved.
The application provides an inquiry processing method, an inquiry data processing method and a device, which are realized as follows:
an interrogation treatment method comprising:
receiving disease description data to be displayed;
displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data;
acquiring operation behavior data of a user on a target object;
and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
An interrogation data processing method comprising:
acquiring disease description data input by a user;
identifying a target object from the disease description data according to a preset rule;
and sending the disease condition description data to a doctor end for displaying, and displaying the target object in the disease condition description data in a marker guide mode during displaying.
An interrogation processing apparatus comprising:
the receiving module is used for receiving disease description data to be displayed;
the first display module is used for displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of a patient in the disease condition description data;
the acquisition module is used for acquiring operation behavior data of a user on a target object;
and the second display module is used for displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
A terminal device comprising a processor and a memory for storing processor-executable instructions, the instructions when executed by the processor implementing the steps of the method of:
receiving disease description data to be displayed;
displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data;
acquiring operation behavior data of a user on a target object;
and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
A computer readable storage medium having stored thereon computer instructions which, when executed, implement the steps of a method comprising:
receiving disease description data to be displayed;
displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data;
acquiring operation behavior data of a user on a target object;
and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
According to the data processing method, the data which can directly represent the illness state of the patient in the illness state description data is displayed in a mark guiding mode, and when the operation behavior of a user on a certain target object meets the preset condition, the display of the knowledge content related to the target object is triggered. Through this kind of mode, can promote the speed that doctor end obtained the information to solved current online inquiry in the short time, the problem that the key information can't be determined to doctor node high efficiency has reached the effect that can accomplish the reading to key information high efficiency, thereby has promoted inquiry efficiency.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.
FIG. 1 is an architectural diagram of an interrogation platform system provided herein;
FIG. 2 is a schematic illustration of an interface provided herein for highlighting entity words;
FIG. 3 is a schematic interface diagram of a text display interface displaying knowledge content associated with entity words provided by the present application;
FIG. 4 is a schematic view of the data flow and processing in the interrogation process provided herein;
FIG. 5 is a method flow diagram of one embodiment of an interrogation processing method provided herein;
fig. 6 is a block diagram of a hardware structure of a computer terminal of an inquiry processing method provided in the present application;
fig. 7 is a block diagram of the structure of the inquiry processing device provided in the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Aiming at the problems of the existing image-text inquiry, the words which need to be read by a doctor are large, thereby seriously influencing the inquiry efficiency. Therefore, in consideration of reading habits of people, characters are not read word by word generally according to a sequence, an important sentence is selected, if a sentence is read, an important word is selected, and if a word is read, the other radicals of the Chinese character can be scanned with emphasis. The ability of selecting key contents for reading is naturally formed after long-term reading training of people in order to improve the reading efficiency.
Based on this, if the eyes can be guided to locate important information points by a method of key marks, the time for the doctor to filter the information through the eyes can be saved, the reading speed can be increased, and the attention of the doctor can be focused on the more important information.
In this example, an interrogation platform system is provided, as shown in fig. 1, which may include: user 101, server 102, doctor 103.
The user 101 may be a person in need of an inquiry, for example, the patient himself or herself, or a person assisting the inquiry. The specific type of the user can be set according to the actual scene and situation, which is not limited in the present application.
A user 101 logs in an inquiry platform and can input or upload disease description information, wherein the disease description information can be a segment of characters and can also be in the forms of characters and pictures; the disease description information can be input by the user, or automatically generated by the system according to the information previously input by the user, or generated by combining the basic information previously input by the user and the information currently input by the user.
The doctor 103 may generate inquiry result information from the medical condition instruction information, return the inquiry result information to the server 102, and return the inquiry result information to the user 101 via the server 102.
For example: the disease description information input by the user is as follows: the patient feels uncomfortable throat and often coughs before five days, and the Sanjiu Ganmaoling is taken at home by himself, but the disease condition is not improved. At this time, the information input by the user can be used as inquiry information, and some basic information before the user can be added, such as: zhang three, age 29, male, etc., which are sent to the doctor together with the combined information as the inquiry information in the user input information.
Specifically, the generation and the demand of the inquiry information can be set according to the actual situation and the needs, which is not limited in the present application. For example, if it is considered that only the currently submitted information is sufficient, the currently submitted information may be used as the inquiry information, and if it is considered that the basic information of the user or the information available on the platform needs to be added, the information may be called and added to the information currently submitted by the user.
After the information to be displayed (i.e., the above-mentioned disease description information) is obtained, the information to be displayed may be processed to identify data in which the disease condition of the patient may be directly characterized, that is, important data that is advantageous for a doctor to quickly determine the disease condition of the patient. Therefore, entity words can be selected as the data, namely, the disease condition data information is subjected to entity identification to obtain the disease condition data information after the entity identification. For example, a dictionary can be set, after the data is subjected to word segmentation processing, matching can be performed in a preset dictionary, and the entity words falling into the dictionary are used as the target objects of the data capable of directly representing the patient condition. When the data requiring the highlight display is displayed on the doctor side with the important entity information as the data requiring the highlight display, for example, the doctor 103 side can display the medical explanation information and highlight the entity word.
For example, the data may be displayed in a highlighted manner, in a bold manner, or in a manner of displaying in different colors, as long as the information can be highlighted, the data may be displayed in a manner of highlighting, and in an actual scene, the highlighting may be selected and set according to actual requirements, which is not limited in the present application.
Specifically, in order to determine the data that needs to be displayed with the key marks, the data can be displayed in an entity recognition mode, that is, the information to be displayed is subjected to word segmentation, then the result obtained by word segmentation is compared with a preset dictionary, and if words in the preset dictionary exist in the word segmentation result, the words in the dictionary are used as the data that needs to be displayed with the key marks. The preset dictionary may be, for example: the knowledge graph can also be an excel table or a data set comprising a plurality of words. In practical implementation, which mode is selected as the preset dictionary can be selected according to actual needs or actual scenes, and the method is not limited in the application.
For example, if a knowledge map is generally present in the medical field of an inquiry, the knowledge map may be used as a predetermined dictionary. After the illness state description information input by the user is obtained, word segmentation processing can be carried out on the illness state data information to obtain a plurality of word segmentation results, then entity recognition is carried out on each word in the word segmentation results through a knowledge map, so that words needing highlight display in the illness state data information can be obtained, through highlight display of the words, a doctor can more quickly finish browsing the whole illness state data information, and therefore the inquiry efficiency of the doctor can be effectively improved.
Considering that a user sometimes inputs wrongly written characters due to carelessness or urgent and other factors when inputting data to be displayed, in order to reduce the influence of the wrongly written characters on the browsing of information by a browser, before performing word segmentation processing, error correction processing can be performed on a text, namely, the wrongly written characters in the data to be displayed are determined, and the wrongly written characters are automatically calibrated, so that the reading efficiency is not influenced by the wrongly written characters when the browser browses the data. By the method, the browsing time of a browser can be effectively reduced, and if a doctor asks for a doctor, the text error correction function is integrated, so that the inquiry efficiency of the doctor can be effectively improved.
Namely, the point of the eye positioning is guided by the way of the key mark, so that the time for filtering information by the eye itself can be saved, the reader can focus on the relatively important information, and the reading efficiency can be accelerated.
For example, the user inputs that the user falls hurt in a football game 6 months ago, has swollen thighs and has pain to go to northern three hospitals orthopedics car inspection after the user nurses at home for 3 days, determines that the leg bone fracture is treated by operation, and uses the tiger bone plaster in cooperation after the operation. The contents of the operation part of the last few days that some legs are swollen and painful, the skin is bluish purple, and whether the skin is related to the previous bone fracture or not are taken as the disease description information.
The disease condition description information is subjected to word segmentation, then, the entity data in the disease condition description information can be determined in a knowledge map mode, and the determined entity data can be highlighted, for example, the word size or the color of the identified entity data can be different from that of the other entity data as shown in fig. 2, so that a browser can read the entity data more efficiently, and the inquiry efficiency is improved. Namely, the user A inputs disease description information that the user A falls and injures in a football match 6 months before himself, the thigh swelling is hard to endure to northern three-hospital orthopedic examination after being maintained at home for 3 days, the leg bone fracture is confirmed and is treated by surgery, and the tiger bone plaster is used in cooperation after the surgery. The operation part is preferentially swollen and painful on legs in recent days, the skin is bluish purple and is related to the previous bone fracture, when the information of the text on the doctor side is displayed, the recognized entity words are '6 months ago, swollen thighs, northern three hospitals orthopedics, bone fracture of legs, operation treatment, tiger bone paste, swollen legs and painful', and then when the disease description information is displayed, the entity words can be displayed in a highlighted display mode.
In practical implementations, the highlighting may be by, for example: the information is highlighted or displayed in a more vivid color, for example, in the case that the general information is displayed in black, the content to be highlighted may be displayed in yellow, red, blue, etc., which may make the information more prominent.
Further, it is considered that in an actual application scenario, when the information to be displayed is displayed, sometimes a viewer wants to query the concepts of some terms in the information, that is, needs to refer to relevant data so as to understand or make a judgment more easily. For this reason, in this example, in consideration of the fact that the entity data is already identified when the information to be displayed is displayed, the data searched by the internet or the data matched in the knowledge base can be matched for each entity in advance as the knowledge content associated with the entity word. When the display is triggered, some conditions for triggering the display may be set, for example, if the cursor stays at the position corresponding to the target word for a predetermined time, the knowledge content associated with the target word may be displayed on the current interface in a manner of a pop-up window, or if the target word is clicked, the knowledge content associated with the target word may be displayed on the current interface in a manner of a pop-up window, or the like.
In order to display the associated knowledge content, the associated knowledge content may be displayed in a pop-up window manner or a floating window manner, and if the pop-up window or the floating window is clicked, the associated knowledge content may be displayed in a full screen manner, which is a specific display manner.
The associated knowledge content generated for the entity word can be generated in advance and then cached, but this will result in wasting cache resources. Even real-time match finding can meet the requirements considering that the current network speed or the processing speed of a processor are very fast. Therefore, the generation of the associated knowledge content for the entity word may be triggered when it is determined that the user has a search intention, for example, if the retention time of the mouse of the user on the target entity word is longer than a preset time, the associated knowledge content is actively matched for the target entity word in real time. Or, in combination with the existing gaze tracking technology, when it is determined that the stay time of the line of sight of the viewer on the entity word reaches a preset time, the associated knowledge content is triggered to be matched in real time.
For example, as shown in fig. 2, the user inputs that "i fall hurt in a football game 6 months ago, the thigh swelling is hard to endure to the northern three hospitals orthopedics car inspection after the home maintenance for 3 days, the leg bone fracture is determined and the operation treatment is performed, and the tiger bone plaster is used in cooperation after the operation. The contents of the operation part of the last few days that some legs are swollen and painful, the skin is bluish purple, and whether the skin is related to the previous bone fracture or not are taken as the disease description information. If the stay time of the user in the word of 'leg swelling' exceeds the preset time length or the user clicks the word of 'leg swelling', the relevant knowledge of the word of 'leg swelling' can be matched and displayed on the current interface. For example, the related knowledge of the cluttering word may be displayed in the current interface in a hanging or floating window manner, as shown in fig. 3. For example: symptoms associated with leg swelling (excess fluid accumulates in the interstitial spaces between the legs and the vessels, resulting in an increase in volume of normal leg tissue due to excess fluid, known as edema in the lower limbs, lymphoedema, and inflammatory edema), and office visits (recommended office cardiology, gastroenterology, nephrology, endocrinology, vascular surgery), or may be a point-and-click remission.
In the above example, the inquiry platform is taken as an example for explanation, and the method can be applied not only in the inquiry scene, but also in other scenes, such as: announcements, product introductions, displays of shopping reviews, etc., may all be used in this manner. That is, for the content to be displayed, word segmentation processing and entity recognition may be performed according to the corresponding direction or field, and then, during the display, the recognized field entity content is highlighted. Therefore, when the user watches the announcement, the comments and the product introduction, the key points of the content can be determined more easily, and the reading efficiency can be improved.
Taking a specific scenario as an example, taking an inquiry of a patient on an inquiry platform as an example, a doctor serves as a provider of an inquiry service in the inquiry platform, the platform distributes a videotext inquiry task of the patient to the doctor, and the doctor performs to complete the inquiry task. In this process, doctors need to spend time reading the information such as disease description and images provided by patients, then analyzing the disease, looking up the information, and after obtaining the inquiry result, feeding the result back to the patients in a text mode.
In this process, the doctor needs time to read the patient's description of the condition and review the data. If the efficiency of the doctor for reading the disease description or the efficiency of consulting the data can be improved, the efficiency of the doctor for seeing the doctor can be effectively improved. At the time of inquiry, doctors often need to read a large number of disease descriptions in a short time, because the time is limited, the information reading is lost, and sometimes the time is also needed to inquire about related diseases or medicine information to confirm the scheme, and if the time is too long, the satisfaction degree of the patients is affected. Therefore, in the embodiment, the entity is identified through the existing knowledge map library, the acquisition of the description important information of the patient by the doctor is increased in a bionic reading mode, and meanwhile, the content of available knowledge bases (disease encyclopedia, medicine instruction manual) for diseases, medicines and the like is taken as a support, so that the inquiry processing time of the doctor is shortened, and the satisfaction degree of the patient is improved.
Furthermore, considering that the patient can hardly have wrongly written words and the like when inputting the extensive disease description information, the difficulty of acquiring information by the doctor is increased in a limited time, and therefore, the method can correct the words of the disease description information input by the patient, and then perform word segmentation and entity recognition based on the corrected text content, thereby avoiding the problem that the understanding difficulty of the doctor is increased due to the input of the wrong words.
After the patient submits the image-text inquiry order, the inquiry platform or the server can carry out interaction so as to realize on-line inquiry. Specifically, as shown in fig. 4, the patient, the server, and the doctor may interact according to the following steps:
s1: the patient submits an inquiry order and completes the self-statement of the disease condition;
s2: forming a bionic marking example in the server according to the disease condition, and storing the bionic marking example in an inquiry database;
specifically, the forming of the bionic annotation instance in the server may include:
s2-1: the server corrects the text of the word number content of the disease condition so as to process wrongly written words in the word number content of the disease condition;
s2-2: performing word segmentation processing on the corrected text, and identifying stop words in the text;
s2-3: after word segmentation, entity recognition and labeling are performed, for example: the following can be identified and noted: physical content such as body part, disease symptoms, hospital departments, treatments and drugs, time, etc.;
s2-4: retrieving a database of entities and linking the entities with a knowledge base, wherein the knowledge base may comprise: disease encyclopedia, vaccine encyclopedia, drug instruction book, etc.;
s3: the doctor client reads data through the front end;
s4: rendering and marking are carried out at the front end;
s5: the doctor reads the text content after the rendering and marking, and can obtain the knowledge base content of the relevant entity through operations such as mouse hovering or clicking and the like so as to form an inquiry result.
In the above example, the point of eye location is guided by the method of key mark, so as to save the time for filtering information by the eyes themselves, thereby being used for accelerating reading and putting reading energy on important information. Furthermore, the knowledge graph of the health industry is utilized to perform entity recognition and labeling on the self-describing content of the patient, the knowledge base is linked and displayed to the doctor through a bionic reading means, so that the doctor can be accelerated to obtain important user information, the health knowledge base is linked through the entity, important information such as diseases and specifications can be simply and rapidly obtained, the reading time and the information preparation time can be saved, and the user satisfaction is improved. In this example, there is provided a data processing method, which may include:
step 1: acquiring text data to be displayed;
step 2: extracting a target processing object of the text data to be displayed;
specifically, when the target processing object recognition is performed on the text data to be displayed, an entity recognition mode may be adopted, for example, word segmentation processing may be performed on the text data to be displayed first; and then, carrying out entity recognition on the text data after word segmentation processing through a preset dictionary so as to recognize entity words in the text data after word segmentation processing. Wherein the preset dictionary may include, but is not limited to, at least one of: knowledge map, domain dictionary and preset word library.
Considering that input text data to be displayed sometimes has input errors, in order to reduce reading difficulty, error correction processing can be performed on the text data to be displayed firstly; and then carrying out entity recognition on the text data after error correction processing.
Furthermore, when a user reads text data to be displayed, a need sometimes exists for searching some contents in the text data, and therefore, after the entity words in the text data to be displayed are identified, a knowledge base can be called; determining knowledge content of each identified entity word in the knowledge base in a relevant manner; correspondingly, in the process of displaying the text data to be displayed, the method may further include: detecting the operation behavior of a user on a target entity word; and under the condition that the operation behavior of the user on the target entity word is determined to meet the preset condition, displaying the knowledge content associated with the target entity word in an interface for displaying the text data to be displayed. Therefore, when reading, text search is not needed independently, and the associated content of the entity content expected to be searched can be obtained only in the current display interface, so that the efficiency of the whole reading and understanding process is improved.
Wherein, the preset condition may include but is not limited to at least one of the following: clicking the target entity word, wherein the time for the sight line to stay on the target entity word exceeds a first preset time length, and the time for the mouse to stay on the target entity word exceeds a second preset time length.
And step 3: and displaying the target processing object according to a preset display mode, wherein the preset display mode comprises a mark guide mode.
Wherein, the mark guide mode display may include but is not limited to at least one of the following: highlight display, bold display and color display. By highlighting, a browser can acquire the key information in the text data more quickly and can read and understand the content of the text data more efficiently.
In the above example, after the text data to be displayed is acquired, the target processing object is extracted first, and then the target processing object is displayed in a mark guidance manner in the display process. Because the target processing object is specially displayed, attention can be paid to the target processing object more quickly when text data to be displayed are browsed, the problem that key information cannot be determined quickly and efficiently when the information is read in the existing short time is solved, the effect that reading of the key information can be completed quickly and efficiently is achieved, reading efficiency is improved, and event processing efficiency is improved.
The data processing method can be applied in the scene of inquiry, and can also be applied to the following fields: announcements, product introductions, display of shopping reviews, and the like. That is, for the content to be displayed, word segmentation processing and entity recognition may be performed according to the corresponding direction or field, and then, during the display, the recognized field entity content is highlighted. Therefore, when the user watches the announcement, the comments and the product introduction, the key points of the content can be determined more easily, and the reading efficiency can be improved.
Taking application in an inquiry scene as an example, in this example, an inquiry processing method is provided, which may include:
s1: acquiring disease description data input by a user;
s2: extracting a target processing object in the disease description data;
s3: and displaying the target processing object according to a preset display mode, wherein the preset display mode comprises a mark guide mode.
Wherein extracting the target processing object in the condition description data may include: performing word segmentation processing on the disease description data; performing entity recognition on the text data after the word segmentation processing through a preset dictionary; and taking the identified entity words as the target processing objects. Wherein the preset dictionary may include, but is not limited to, at least one of: symptom knowledge map, medical dictionary, diagnosis and treatment word library and hospital department classification table.
After identifying the entity words in the disease description data, a medical field knowledge base can be called; determining the related knowledge content of each identified entity word in the medical field knowledge base; correspondingly, in the process of displaying the disease description data, the method further comprises the following steps: detecting the operation behavior of a user on a target entity word; and under the condition that the operation behavior of the user on the target entity word is determined to meet the preset condition, displaying the knowledge content associated with the target entity word in an interface for displaying the disease condition description data.
In practical implementation, the processing and displaying processes may not be implemented in one device, for example, the processing is implemented in one device, and the display device only performs a displaying function, so that for the processing device, the disease description data input by the user may be obtained; performing entity recognition on the disease condition description data to identify entity words in the disease condition description data; associating knowledge content for the identified entity words from the knowledge base; the disease description data, the identified entity words, and the associated knowledge content are stored as examples. For the stored instance, the display may be performed in a display device.
Based on the inquiry scenario, in this example, an inquiry processing method is provided, and for the doctor end, as shown in fig. 5, the method includes the following steps:
step 501: receiving disease description data to be displayed;
the disease description data to be displayed may be transmitted after the server-side processing is completed, and specifically, the server may perform the following processing: performing word segmentation processing on the disease description data; performing entity recognition on the text data after the word segmentation processing through a preset dictionary; and taking the identified entity words as the target objects.
Wherein the preset dictionary may include, but is not limited to, at least one of: symptom knowledge map, medical dictionary, diagnosis and treatment word library and hospital department classification table.
When the disease condition description data is subjected to word segmentation, the disease condition description data can be subjected to error correction, and then the disease condition description data subjected to error correction is subjected to word segmentation.
Step 502: displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data;
wherein, the manner of the mark guide may include but is not limited to at least one of the following: highlight display, bold display and color display. Through the mark guiding mode, a doctor can acquire more useful data in a shorter time when browsing the disease description data, so that the efficiency of inquiry is improved.
Step 503: acquiring operation behavior data of a user on a target object;
step 504: and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
Specifically, displaying the knowledge content associated with the target object oriented to the operation behavior data may be calling a medical field knowledge base; determining the associated knowledge content of the target object oriented to the operation behavior data in the medical field knowledge base; and determining the knowledge content associated with the target object oriented to the operation behavior data in the medical field knowledge base to be displayed.
Wherein the preset condition may include, but is not limited to, at least one of the following: clicking the target object, enabling the sight line to stay on the target object for more than a first preset time length, and enabling the mouse to stay on the target object for more than a second preset time length. That is, as long as the operation can represent that there is a detailed understanding requirement, the operation can be used as a preset condition to display the associated knowledge content.
In this example, there is also provided an inquiry data processing method, located at the server side, which may include the following steps:
s1: acquiring disease description data input by a user;
s2: identifying a target object from the disease description data according to a preset rule;
s3: and sending the disease condition description data to a doctor end for displaying, and displaying the target object in the disease condition description data in a marker guide mode during displaying.
After the target object is identified from the disease description data according to a preset rule, a preset knowledge base can be called; matching knowledge contents associated with each target object from the knowledge base; and storing the disease condition description data, the identified target objects and the associated knowledge content of each target object as an example. Specifically, matching the knowledge content associated with each target object from the knowledge base may include: marking each identified target object; according to the labeling result, matching with the link content associated with each label preset in the knowledge base; and taking the matching result as the associated knowledge content of each determined target object in the knowledge base.
The method embodiments provided in the above embodiments of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking the computer terminal as an example, fig. 6 is a hardware structure block diagram of the computer terminal of the inquiry processing method provided in the present application. As shown in fig. 6, the computer terminal 10 may include one or more processors 02 (only one is shown in the figure) (the processor 02 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 04 for storing data, and a transmission module 06 for communication functions. It will be understood by those skilled in the art that the structure shown in fig. 6 is only an illustration and is not intended to limit the structure of the electronic device. For example, the computer terminal 10 may also include more or fewer components than shown in FIG. 6, or have a different configuration than shown in FIG. 6.
The memory 04 may be used to store software programs and modules of application software, such as program instructions/modules corresponding to the inquiry processing method in the embodiment of the present application, and the processor 02 executes various functional applications and data processing by running the software programs and modules stored in the memory 04, that is, implements the inquiry processing method of the application program. The memory 04 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 04 may further include memory located remotely from the processor 02, which may be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission module 06 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission module 06 includes a Network adapter (NIC) that can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission module 06 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In terms of software, the above-mentioned inquiry processing device may be as shown in fig. 7, and includes:
a receiving module 701, configured to receive disease description data to be displayed;
a first display module 702, configured to display, in a marker-guided manner, a target object in the disease condition description data, where the target object is data that can directly represent a disease condition of a patient in the disease condition description data;
an obtaining module 703, configured to obtain operation behavior data of a user on a target object;
a second display module 704, configured to display the knowledge content associated with the target object oriented by the operation behavior data when the operation behavior data meets a preset condition.
In one embodiment, the preset condition may include, but is not limited to, at least one of the following: clicking the target object, enabling the sight line to stay on the target object for more than a first preset time length, and enabling the mouse to stay on the target object for more than a second preset time length.
In one embodiment, the second display module 704 may be specifically configured to retrieve a knowledge base of the medical field; determining the associated knowledge content of the target object oriented to the operation behavior data in the medical field knowledge base; and determining the knowledge content associated with the target object oriented to the operation behavior data in the medical field knowledge base to be displayed.
In one embodiment, the above-mentioned way of guiding the mark may include, but is not limited to, at least one of the following: highlight display, bold display and color display.
In one embodiment, the target object in the disease description data may be determined as follows:
performing word segmentation processing on the disease description data;
performing entity recognition on the text data after the word segmentation processing through a preset dictionary;
and taking the identified entity words as the target objects.
In one embodiment, the preset dictionary may include, but is not limited to, at least one of: symptom knowledge map, medical dictionary, diagnosis and treatment word library and hospital department classification table.
In one embodiment, the word segmentation process is performed on the disease condition description data, which may be to perform an error correction process on the disease condition description data; and then the disease description data after error correction processing is subjected to word segmentation processing.
An embodiment of the present application further provides a specific implementation manner of an electronic device, which is capable of implementing all steps in the inquiry processing method in the foregoing embodiment, where the electronic device specifically includes the following contents: a processor (processor), a memory (memory), a communication Interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete mutual communication through the bus; the processor is configured to call a computer program in the memory, and when executing the computer program, the processor implements all the steps in the data processing method in the foregoing embodiments, for example, when executing the computer program, the processor implements the following steps:
the following steps are realized:
step 1: receiving disease description data to be displayed;
step 2: displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data;
and step 3: acquiring operation behavior data of a user on a target object;
and 4, step 4: and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
As can be seen from the above description, in the embodiment of the present application, data that can directly represent the disease condition of the patient in the disease condition description data is displayed in a manner of label guidance, and when the operation behavior of the user on a certain target object meets a preset condition, the display of the knowledge content associated with the target object is triggered. Through this kind of mode, can promote the speed that doctor end obtained the information to solved current online inquiry in the short time, the problem that the key information can't be determined to doctor node high efficiency has reached the effect that can accomplish the reading to key information high efficiency, thereby has promoted inquiry efficiency.
An embodiment of the present application further provides a computer-readable storage medium capable of implementing all the steps in the inquiry processing method in the above embodiment, where the computer-readable storage medium stores thereon a computer program, and when the computer program is executed by a processor, the computer program implements all the steps in the inquiry processing method in the above embodiment, for example, when the processor executes the computer program, the processor implements the following steps:
step 1: receiving disease description data to be displayed;
step 2: displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data;
and step 3: acquiring operation behavior data of a user on a target object;
and 4, step 4: and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
As can be seen from the above description, in the embodiment of the present application, data that can directly represent the disease condition of the patient in the disease condition description data is displayed in a manner of label guidance, and when the operation behavior of the user on a certain target object meets a preset condition, the display of the knowledge content associated with the target object is triggered. Through this kind of mode, can promote the speed that doctor end obtained the information to solved current online inquiry in the short time, the problem that the key information can't be determined to doctor node high efficiency has reached the effect that can accomplish the reading to key information high efficiency, thereby has promoted inquiry efficiency.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to the partial description of the method embodiment.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Although the present application provides method steps as described in an embodiment or flowchart, additional or fewer steps may be included based on conventional or non-inventive efforts. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or client product executes, it may execute sequentially or in parallel (e.g., in the context of parallel processors or multi-threaded processing) according to the embodiments or methods shown in the figures.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
Although embodiments of the present description provide method steps as described in embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or end product executes, it may execute sequentially or in parallel (e.g., parallel processors or multi-threaded environments, or even distributed data processing environments) according to the method shown in the embodiment or the figures. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded.
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, in implementing the embodiments of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, and the like. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may therefore be considered as a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The embodiments of this specification may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The described embodiments may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
The above description is only an example of the embodiments of the present disclosure, and is not intended to limit the embodiments of the present disclosure. Various modifications and variations to the embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification should be included in the scope of the claims of the embodiments of the present specification.
Claims (14)
1. An interrogation treatment method, comprising:
receiving disease description data to be displayed;
displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data;
acquiring operation behavior data of a user on a target object;
and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
2. The method of claim 1, wherein the preset condition comprises at least one of: clicking the target object, enabling the sight line to stay on the target object for more than a first preset time length, and enabling the mouse to stay on the target object for more than a second preset time length.
3. The method of claim 1, wherein displaying knowledge content associated with the target object to which the operational behavior data is directed comprises:
calling a medical field knowledge base;
determining the associated knowledge content of the target object oriented to the operation behavior data in the medical field knowledge base;
and determining the knowledge content associated with the target object oriented to the operation behavior data in the medical field knowledge base to be displayed.
4. The method of claim 1, wherein the manner in which the indicia is guided comprises at least one of: highlight display, bold display and color display.
5. The method of claim 1, wherein the target object in the condition description data is determined as follows:
performing word segmentation processing on the disease description data;
performing entity recognition on the text data after the word segmentation processing through a preset dictionary;
and taking the identified entity words as the target objects.
6. The method of claim 5, wherein the preset dictionary comprises at least one of: symptom knowledge map, medical dictionary, diagnosis and treatment word library and hospital department classification table.
7. The method of claim 5, wherein the tokenizing the condition description data comprises:
carrying out error correction processing on the disease description data;
and performing word segmentation processing on the disease description data subjected to error correction processing.
8. An inquiry data processing method, comprising:
acquiring disease description data input by a user;
identifying a target object from the disease description data according to a preset rule;
and sending the disease condition description data to a doctor end for displaying, and displaying the target object in the disease condition description data in a marker guide mode during displaying.
9. The method of claim 8, further comprising, after identifying the target object from the condition description data according to a predetermined rule:
calling a preset knowledge base;
matching knowledge contents associated with each target object from the knowledge base;
and storing the disease condition description data, the identified target objects and the associated knowledge content of each target object as an example.
10. The method of claim 9, wherein matching knowledge content associated with each target object from the knowledge base comprises:
marking each identified target object;
according to the labeling result, matching with the link content associated with each label preset in the knowledge base;
and taking the matching result as the associated knowledge content of each determined target object in the knowledge base.
11. The method of claim 8, wherein identifying the target object from the condition description data according to a predetermined rule comprises:
performing word segmentation processing on the disease description data;
performing entity recognition on the text data after the word segmentation processing through a preset dictionary;
and taking the identified entity words as the target objects.
12. An interrogation processing apparatus, comprising:
the receiving module is used for receiving disease description data to be displayed;
the first display module is used for displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of a patient in the disease condition description data;
the acquisition module is used for acquiring operation behavior data of a user on a target object;
and the second display module is used for displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
13. A terminal device comprising a processor and a memory for storing processor-executable instructions, the instructions when executed by the processor implementing the steps of the method of:
receiving disease description data to be displayed;
displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data;
acquiring operation behavior data of a user on a target object;
and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
14. A computer readable storage medium having stored thereon computer instructions which, when executed, implement the steps of a method comprising:
receiving disease description data to be displayed;
displaying a target object in the disease condition description data in a marker-guided manner, wherein the target object is data which can directly represent the disease condition of the patient in the disease condition description data;
acquiring operation behavior data of a user on a target object;
and displaying the knowledge content associated with the target object oriented to the operation behavior data under the condition that the operation behavior data meets the preset condition.
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