CN113626688A - Intelligent medical data acquisition method and system based on software definition - Google Patents
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Abstract
The intelligent medical data acquisition method and system based on software definition provided by the application can output a medical description content vector correction training model to display medical description content vectors of a plurality of medical description content labels corresponding to medical users respectively, can freely determine the medical description content labels, can directly update medical user data and determine each medical user content by using the medical user content after determining a target medical description content vector in response to a screening signal of the medical description content labels, can search the spatial positions of a plurality of corresponding simulation objects in the medical users according to the medical user content without searching the medical users, and compared with the mode that a plurality of simulation medical description contents required to be checked are searched at present and the user content corresponding to one corresponding medical description content vector is sequentially acquired among the plurality of simulation medical description contents, the time taken to acquire user content of a plurality of simulated medical descriptive content is reduced.
Description
Technical Field
The application relates to the technical field of data acquisition, in particular to an intelligent medical data acquisition method and system based on software definition.
Background
With the continuous progress of information technology, medical data are continuously increased in an increasing mode, in the traditional medical room data acquisition technology, the acquisition of relevant medical data is difficult and time is wasted, the relevant medical data cannot be acquired in time, the relevant medical data are acquired through artificial intelligence, the efficiency of acquiring the relevant medical data can be effectively improved, and certain defects exist in the artificial intelligence medical data acquisition technology.
Disclosure of Invention
In view of this, the present application provides an intelligent medical data collection method and system based on software definition.
In a first aspect, an intelligent medical data acquisition method based on software definition is provided, the method comprising:
acquiring an intelligent input signal of a user, and outputting a medical description content vector correction training model, wherein the medical description content vector correction training model comprises a plurality of medical description content labels, and the plurality of medical description content labels respectively correspond to medical description content vectors of different simulated medical description contents in a medical user;
responding to screening signals of the plurality of medical description content labels displayed by the medical description content vector correction training model, and determining a target medical description content vector corresponding to the medical description content label under a preset type;
and updating medical user data acquired by a medical set by using the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content.
Further, the acquiring an intelligent input signal of a user and outputting a vector correction training model of medical description content includes:
displaying a user intelligent representation label at a medical treatment collection front end;
and responding to the input signal of the intelligent representation label of the user, and outputting a medical description content vector correction training model.
Further, the determining, in response to the filtering signal of the plurality of medical description content labels displayed by the medical description content vector modification training model, a target medical description content vector corresponding to the medical description content label belonging to a preset type includes:
acquiring abnormal target signals for executing at least two medical description content labels which belong to a preset type and are displayed by the vector correction training model;
and/or acquiring normal target signals for executing at least two medical description content labels which are not in a preset type and are displayed by the vector correction training model;
determining a target medical description content vector corresponding to the medical description content label updated to the preset type in response to the acquired screening signal; wherein the acquired screening signal comprises the abnormal target signal and/or the normal target signal;
wherein, the updating the medical user data collected by the medical collection by using the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content comprises:
and for the medical user data acquired by the medical set, canceling the display of the medical user content corresponding to the medical description content label executing the abnormal target signal, and enhancing the display of the medical user content corresponding to the medical description content label executing the normal target signal.
Further, the updating, by using the medical user content corresponding to the determined target medical description content vector, the medical user data collected by the medical collection, and displaying the medical user content includes:
updating a medical acquisition matrix according to the determined target medical description content vector;
converting a first target medical description content vector newly loaded in an updated medical acquisition matrix and/or a second target medical description content vector which belongs to an unidentified state and is loaded in the medical acquisition matrix before updating into an identified state, and displaying medical user content corresponding to the corresponding target medical description content vector converted into the identified state in medical user data of a medical set;
acquiring a medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating, belongs to an identification state and is different from the target medical description content vector;
and canceling the identification state of the medical description content vector to be deleted so as to cancel the display of the medical user content corresponding to the medical description content vector to be deleted in the medical user data of the medical collection.
Further the method further comprises:
dynamically displaying the medical description content labels of the simulated medical description content contained in the corresponding data set in the medical user data collected by the medical set;
wherein the method further comprises:
displaying a medical data compression range at the medical collection, wherein the medical data compression range includes at least two simulated interval boundaries determined based on a medical user protocol;
and dynamically displaying the spatial position change of the target simulated medical description content in the medical data compression range, wherein the target simulated medical description content refers to the simulated medical description content contained in the medical user content corresponding to the target medical description content vector.
In a second aspect, an intelligent medical data acquisition system based on software definition is provided, which includes a data acquisition device and an intelligent data processing terminal, where the data acquisition device is in communication connection with the intelligent data processing terminal, and the intelligent data processing terminal is specifically configured to:
acquiring an intelligent input signal of a user, and outputting a medical description content vector correction training model, wherein the medical description content vector correction training model comprises a plurality of medical description content labels, and the plurality of medical description content labels respectively correspond to medical description content vectors of different simulated medical description contents in a medical user;
responding to screening signals of the plurality of medical description content labels displayed by the medical description content vector correction training model, and determining a target medical description content vector corresponding to the medical description content label under a preset type;
and updating medical user data acquired by a medical set by using the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content.
Further, the data intelligent processing terminal is specifically configured to:
displaying a user intelligent representation label at a medical treatment collection front end;
and responding to the input signal of the intelligent representation label of the user, and outputting a medical description content vector correction training model.
Further, the data intelligent processing terminal is specifically configured to:
acquiring abnormal target signals for executing at least two medical description content labels which belong to a preset type and are displayed by the vector correction training model;
and/or acquiring normal target signals for executing at least two medical description content labels which are not in a preset type and are displayed by the vector correction training model;
determining a target medical description content vector corresponding to the medical description content label updated to the preset type in response to the acquired screening signal; wherein the acquired screening signal comprises the abnormal target signal and/or the normal target signal;
the data intelligent processing terminal is specifically used for:
and for the medical user data acquired by the medical set, canceling the display of the medical user content corresponding to the medical description content label executing the abnormal target signal, and enhancing the display of the medical user content corresponding to the medical description content label executing the normal target signal.
Further, the data intelligent processing terminal is specifically configured to:
updating a medical acquisition matrix according to the determined target medical description content vector;
converting a first target medical description content vector newly loaded in an updated medical acquisition matrix and/or a second target medical description content vector which belongs to an unidentified state and is loaded in the medical acquisition matrix before updating into an identified state, and displaying medical user content corresponding to the corresponding target medical description content vector converted into the identified state in medical user data of a medical set;
acquiring a medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating, belongs to an identification state and is different from the target medical description content vector;
and canceling the identification state of the medical description content vector to be deleted so as to cancel the display of the medical user content corresponding to the medical description content vector to be deleted in the medical user data of the medical collection.
Further, the data intelligent processing terminal is specifically configured to:
dynamically displaying the medical description content labels of the simulated medical description content contained in the corresponding data set in the medical user data collected by the medical set;
the data intelligent processing terminal is specifically used for:
displaying a medical data compression range at the medical collection, wherein the medical data compression range includes at least two simulated interval boundaries determined based on a medical user protocol;
and dynamically displaying the spatial position change of the target simulated medical description content in the medical data compression range, wherein the target simulated medical description content refers to the simulated medical description content contained in the medical user content corresponding to the target medical description content vector.
The intelligent medical data acquisition method and system based on software definition provided by the embodiment of the application can perform user intelligent input signals in the medical collection, acquire the user intelligent input signals, output a medical description content vector correction training model to display a plurality of medical description content labels, respectively correspond to medical description content vectors of different simulated medical description contents in medical users according to the plurality of medical description content labels, freely determine the medical description content labels corresponding to the plurality of medical description content vectors to be acquired, respond to screening signals of the medical description content labels, determine a target medical description content vector to be displayed, directly utilize the corresponding medical user content to update the medical user data displayed in the medical collection, display the determined medical user content, and simultaneously view the medical user content corresponding to each of the plurality of screened medical description content vectors according to personal requirements, and the user does not need to search the corresponding spatial positions of the plurality of simulation objects in the medical user, and the time spent on acquiring the user contents of the plurality of simulation medical description contents is shortened compared with the mode that the plurality of simulation medical description contents which need to be checked are searched at present and the user contents corresponding to the corresponding medical description content vector are sequentially acquired among the plurality of simulation medical description contents.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a flowchart of an intelligent medical data acquisition method based on software definition according to an embodiment of the present application.
Fig. 2 is a block diagram of an intelligent medical data acquisition device based on software definition according to an embodiment of the present application.
Fig. 3 is an architecture diagram of an intelligent medical data acquisition system based on software definition according to an embodiment of the present application.
Detailed Description
In order to better understand the technical solutions, the technical solutions of the present application are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.
Referring to fig. 1, an intelligent medical data acquisition method based on software definition is shown, which may include the technical solutions described in the following steps 100-300.
And step 100, acquiring an intelligent input signal of a user, and outputting a medical description content vector correction training model.
Illustratively, the medical description content vector modification training model includes a plurality of medical description content tags, and the plurality of medical description content tags respectively correspond to medical description content vectors of different simulated medical description contents in the medical user.
Illustratively, the target medical descriptive content vector is used to characterize key features in the medical descriptive content tag.
Illustratively, updating medical user data acquired by the medical corpus is used to characterize the acquisition of accurate medical user data.
It can be understood that, when the technical solutions described in steps 100 to 300 are executed, a user intelligent input signal is performed in the medical collection, the user intelligent input signal is obtained, a medical description content vector modification training model is output to display a plurality of medical description content tags, the medical description content vectors corresponding to different simulated medical description contents in the medical users are respectively corresponding to the plurality of medical description content tags, the medical description content tags corresponding to the plurality of medical description content vectors to be acquired can be freely determined, after the target medical description content vector to be displayed is determined in response to the filtering signal for the medical description content tags, the medical user data displayed in the medical collection can be directly utilized, the determined medical user contents are displayed, the respective medical user contents corresponding to the filtered plurality of medical description content vectors can be simultaneously viewed according to personal requirements, and the user does not need to search the corresponding spatial positions of the plurality of simulation objects in the medical user, and the time spent on acquiring the user contents of the plurality of simulation medical description contents is shortened compared with the mode that the plurality of simulation medical description contents which need to be checked are searched at present and the user contents corresponding to the corresponding medical description content vector are sequentially acquired among the plurality of simulation medical description contents.
In an alternative embodiment, the inventor finds that when the user intelligent input signal is acquired, there is a problem that the input signal of the tag is inaccurate, so that it is difficult to accurately output the medical description content vector modification training model, and in order to improve the above technical problem, the step of acquiring the user intelligent input signal and outputting the medical description content vector modification training model described in step 100 may specifically include the technical solutions described in the following step q1 and step q 2.
Step q1, displaying the user intelligent representation label at the front end of the medical collection.
And q2, responding to the input signal of the intelligent representation label of the user, and outputting a medical description content vector correction training model.
It can be understood that when the technical solutions described in the above steps q1 and q2 are executed, when the user intelligent input signal is acquired, the problem of inaccuracy of the input signal of the tag is solved, so that the medical description content vector correction training model can be accurately output.
In an alternative embodiment, the inventor finds that, in response to the filtering signals of the plurality of medical description content tags displayed by the medical description content vector modification training model, there is a problem that the vector modification training model is inaccurate in modification, so that it is difficult to accurately determine the target medical description content vector corresponding to the medical description content tag under the preset type, and in order to improve the above technical problem, the step of determining the target medical description content vector corresponding to the medical description content tag under the preset type in response to the filtering signals of the plurality of medical description content tags displayed by the medical description content vector modification training model, which is described in step 200, may specifically include the technical solutions described in the following steps w 1-w 3.
And step w1, acquiring abnormal target signals for executing at least two medical description content labels of preset types displayed by the vector correction training model.
Step w2, and/or acquiring normal target signals for executing at least two medical description content labels which are not of the preset type and are displayed by the vector correction training model.
Step w3, in response to the obtained screening signal, determining a target medical description content vector corresponding to the medical description content label updated to the preset type; wherein the acquired screening signal comprises the abnormal target signal and/or the normal target signal.
It can be understood that, when the technical solutions described in steps w 1-w 3 are executed, in response to the filtering signals of the plurality of medical description content labels displayed by the medical description content vector correction training model, the problem of inaccurate correction of the vector correction training model is solved, so that the target medical description content vector corresponding to the medical description content label belonging to the preset type can be accurately determined.
In an alternative embodiment, the inventor finds that, when the medical user content corresponding to the determined target medical description content vector is utilized, there is a problem that the display of the medical user content is not accurate, so that it is difficult to accurately update the medical user data collected by the medical collection, and the medical user content is displayed, in order to improve the above technical problem, the step of updating the medical user data collected by the medical collection and displaying the medical user content by utilizing the medical user content corresponding to the determined target medical description content vector, which is described in step 300, may specifically include the technical solution described in step e1 below.
And e1, for the medical user data collected by the medical collection, canceling the display of the medical user content corresponding to the medical description content label executing the abnormal target signal, and enhancing the display of the medical user content corresponding to the medical description content label executing the normal target signal.
It can be understood that, when the technical solution described in step e1 is executed, and the medical user content corresponding to the determined target medical description content vector is utilized, the problem of inaccurate display of the medical user content is improved, so that the medical user data collected by the medical collection can be accurately updated, and the medical user content is displayed.
In an alternative embodiment, the invention finds that, when the medical user content corresponding to the determined target medical description content vector is utilized, there is a problem that the updated medical acquisition matrix is inaccurate, so that it is difficult to accurately update the medical user data acquired by the medical collection and display the medical user content, and in order to improve the above technical problem, the step of updating the medical user data acquired by the medical collection and displaying the medical user content by utilizing the medical user content corresponding to the determined target medical description content vector, which is described in step 300, may specifically include the technical solutions described in the following step r 1-step r 4.
And r1, updating a medical acquisition matrix according to the determined target medical description content vector.
And r2, converting the first target medical description content vector newly loaded in the updated medical acquisition matrix and/or the second target medical description content vector which belongs to the unidentified state and is loaded in the medical acquisition matrix before updating into the identified state, and displaying the medical user content corresponding to the corresponding target medical description content vector converted into the identified state in the medical user data of the medical collection.
And r3, acquiring the medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating, belongs to the identification state and is different from the target medical description content vector.
And r4, canceling the identification state of the medical description content vector to be deleted, so as to cancel the display of the medical user content corresponding to the medical description content vector to be deleted in the medical user data of the medical collection.
It can be understood that when the technical solutions described in the above steps r 1-r 4 are executed, and the medical user content corresponding to the determined target medical description content vector is used, the problem that the medical acquisition matrix is not accurate to update is solved, so that the medical user data acquired by the medical collection can be accurately updated, and the medical user content is displayed.
Based on the above basis, the following technical solution described in step t1 may also be included.
Step t1, dynamically displaying the medical description content label of the simulated medical description content contained in the corresponding data set in the medical user data collected by the medical set.
It can be understood that when the technical solution described in the above step t1 is executed, the accuracy of the medical description content label is improved by dynamic display.
Based on the above basis, the technical scheme described in the following steps y1 and y2 can be further included.
And step y1, displaying the medical data compression range in the medical collection.
For example, the medical data compression range includes at least two simulation interval boundaries determined based on a medical user protocol.
And step y2, dynamically displaying the spatial position change of the target simulation medical descriptive content in the medical data compression range.
For example, the target simulated medical description content refers to simulated medical description content included in medical user content corresponding to the target medical description content vector
It can be understood that when the technical solutions described in the above steps y1 and y2 are executed, the accuracy of dynamically displaying the spatial position change of the target simulation medical descriptive content is improved by displaying the medical data compression range.
Based on the above basis, the technical scheme described in the following step a1 can be further included.
Step a1, determining the number of the target medical description content vectors to be multiple, and obtaining the medical description content spatial position display type corresponding to each of the multiple target medical description content vectors.
It can be understood that, when the technical solution described in the above step a1 is executed, through a plurality of target medical description content vectors, a medical description content spatial position display type corresponding to each of the plurality of target medical description content vectors can be accurately obtained.
In a possible embodiment, the inventor finds that, in the medical data compression range, when the spatial position of the target simulated medical descriptive content is dynamically displayed, there are different target medical descriptive content vectors, so that it is difficult to accurately and dynamically display the spatial position of the target simulated medical descriptive content, and in order to improve the above technical problem, the step of dynamically displaying the spatial position of the target simulated medical descriptive content in the medical data compression range, which is described in step y2, may specifically include the technical solution described in step y21 below.
And y21, controlling the spatial position labels of the simulated medical description contents contained in the medical user contents corresponding to different target medical description content vectors in the medical data compression range to present the corresponding spatial position display types of the medical description contents.
It can be understood that when the technical solution described in the above step y21 is executed, in the medical data compression range, when the spatial position of the target simulated medical descriptive content is dynamically displayed, different target medical descriptive content vectors are improved, so that the spatial position of the target simulated medical descriptive content can be accurately and dynamically displayed.
Based on the above basis, the following technical solutions described in step d1 and step d2 may also be included.
And d1, responding to the screening signal of any simulation interval boundary of the medical data compression range, and determining the user content to be acquired corresponding to the screened simulation interval boundary.
And d2, updating the medical user data collected by the medical collection to the collection of the user content to be collected.
It can be understood that, when the technical solutions described in the above steps d1 and d2 are executed, the accuracy of acquiring the user content to be acquired updated to the user content to be acquired is improved by accurately determining the user content to be acquired corresponding to the filtered simulation interval boundary.
On the basis, please refer to fig. 2 in combination, an intelligent medical data acquisition apparatus 200 based on software definition is provided, which is applied to a data intelligent processing end, and the apparatus includes:
an input signal obtaining module 210, configured to obtain an intelligent input signal of a user, and output a medical description content vector modification training model, where the medical description content vector modification training model includes a plurality of medical description content tags, and the plurality of medical description content tags respectively correspond to medical description content vectors of different simulated medical description contents in a medical user;
the description content determining module 220 is configured to determine, in response to the filtering signals of the plurality of medical description content labels displayed by the medical description content vector modification training model, a target medical description content vector corresponding to the medical description content label belonging to a preset type;
and the user data updating model 230 is configured to update medical user data acquired by the medical collection by using the medical user content corresponding to the determined target medical description content vector, and display the medical user content.
On the basis of the above, please refer to fig. 3, which shows an intelligent medical data acquisition system 300 based on software definition, comprising a processor 310 and a memory 320, which are communicated with each other, wherein the processor 310 is used for reading the computer program from the memory 320 and executing the computer program to implement the above method.
On the basis of the above, there is also provided a computer-readable storage medium on which a computer program is stored, which when executed implements the above-described method.
In summary, based on the above-mentioned solution, a user intelligent input signal is performed in the medical collection, the user intelligent input signal is obtained, a medical description content vector correction training model is output to display a plurality of medical description content tags, the medical description content tags corresponding to a plurality of medical description content vectors to be acquired can be freely determined according to the medical description content vectors of different simulated medical description contents in the medical users corresponding to the plurality of medical description content tags, the target medical description content vector to be displayed is determined in response to the filtering signal for the medical description content tags, and then the medical user data displayed in the medical collection can be updated by directly using the corresponding medical user content, the determined medical user contents are displayed, the respective corresponding medical user contents of the filtered medical description content vectors can be simultaneously viewed according to individual needs, and the user does not need to search the corresponding spatial positions of the plurality of simulation objects in the medical user, and the time spent on acquiring the user contents of the plurality of simulation medical description contents is shortened compared with the mode that the plurality of simulation medical description contents which need to be checked are searched at present and the user contents corresponding to the corresponding medical description content vector are sequentially acquired among the plurality of simulation medical description contents.
It should be appreciated that the system and its modules shown above may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory for execution by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided, for example, on a carrier medium such as a diskette, CD-or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).
It is to be noted that different embodiments may produce different advantages, and in different embodiments, any one or combination of the above advantages may be produced, or any other advantages may be obtained.
Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered merely illustrative and not restrictive of the broad application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.
Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.
Moreover, those skilled in the art will appreciate that aspects of the present application may be illustrated and described in terms of several patentable species or situations, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereon. Accordingly, various aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.
The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.
Computer program code required for the operation of various portions of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, a conventional programming language such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, Ruby, and Groovy, or other programming languages, and the like. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).
Additionally, the order in which elements and sequences of the processes described herein are processed, the use of alphanumeric characters, or the use of other designations, is not intended to limit the order of the processes and methods described herein, unless explicitly claimed. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.
Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.
Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the numbers allow for adaptive variation. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.
The entire contents of each patent, patent application publication, and other material cited in this application, such as articles, books, specifications, publications, documents, and the like, are hereby incorporated by reference into this application. Except where the application is filed in a manner inconsistent or contrary to the present disclosure, and except where the claim is filed in its broadest scope (whether present or later appended to the application) as well. It is noted that the descriptions, definitions and/or use of terms in this application shall control if they are inconsistent or contrary to the statements and/or uses of the present application in the material attached to this application.
Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present application. Other variations are also possible within the scope of the present application. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the present application can be viewed as being consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to only those embodiments explicitly described and depicted herein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. An intelligent medical data acquisition method based on software definition, which is characterized by comprising the following steps:
acquiring an intelligent input signal of a user, and outputting a medical description content vector correction training model, wherein the medical description content vector correction training model comprises a plurality of medical description content labels, and the plurality of medical description content labels respectively correspond to medical description content vectors of different simulated medical description contents in a medical user;
responding to screening signals of the plurality of medical description content labels displayed by the medical description content vector correction training model, and determining a target medical description content vector corresponding to the medical description content label under a preset type;
and updating medical user data acquired by a medical set by using the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content.
2. The method of claim 1, wherein the obtaining of the user intelligent input signal and the outputting of the medical description content vector correction training model comprises:
displaying a user intelligent representation label at a medical treatment collection front end;
and responding to the input signal of the intelligent representation label of the user, and outputting a medical description content vector correction training model.
3. The method according to claim 1, wherein the determining, in response to the filtering signal of the plurality of medical description content labels displayed by the medical description content vector modification training model, a target medical description content vector corresponding to the medical description content label under a preset type includes:
acquiring abnormal target signals for executing at least two medical description content labels which belong to a preset type and are displayed by the vector correction training model;
and/or acquiring normal target signals for executing at least two medical description content labels which are not in a preset type and are displayed by the vector correction training model;
determining a target medical description content vector corresponding to the medical description content label updated to the preset type in response to the acquired screening signal; wherein the acquired screening signal comprises the abnormal target signal and/or the normal target signal;
wherein, the updating the medical user data collected by the medical collection by using the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content comprises:
and for the medical user data acquired by the medical set, canceling the display of the medical user content corresponding to the medical description content label executing the abnormal target signal, and enhancing the display of the medical user content corresponding to the medical description content label executing the normal target signal.
4. The method according to claim 1, wherein the updating the medical user data collected by the medical collection by using the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content comprises:
updating a medical acquisition matrix according to the determined target medical description content vector;
converting a first target medical description content vector newly loaded in an updated medical acquisition matrix and/or a second target medical description content vector which belongs to an unidentified state and is loaded in the medical acquisition matrix before updating into an identified state, and displaying medical user content corresponding to the corresponding target medical description content vector converted into the identified state in medical user data of a medical set;
acquiring a medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating, belongs to an identification state and is different from the target medical description content vector;
and canceling the identification state of the medical description content vector to be deleted so as to cancel the display of the medical user content corresponding to the medical description content vector to be deleted in the medical user data of the medical collection.
5. The method of claim 1, further comprising:
dynamically displaying the medical description content labels of the simulated medical description content contained in the corresponding data set in the medical user data collected by the medical set;
wherein the method further comprises:
displaying a medical data compression range at the medical collection, wherein the medical data compression range includes at least two simulated interval boundaries determined based on a medical user protocol;
and dynamically displaying the spatial position change of the target simulated medical description content in the medical data compression range, wherein the target simulated medical description content refers to the simulated medical description content contained in the medical user content corresponding to the target medical description content vector.
6. The intelligent medical data acquisition system based on software definition is characterized by comprising data acquisition equipment and an intelligent data processing terminal, wherein the data acquisition equipment is in communication connection with the intelligent data processing terminal, and the intelligent data processing terminal is specifically used for:
acquiring an intelligent input signal of a user, and outputting a medical description content vector correction training model, wherein the medical description content vector correction training model comprises a plurality of medical description content labels, and the plurality of medical description content labels respectively correspond to medical description content vectors of different simulated medical description contents in a medical user;
responding to screening signals of the plurality of medical description content labels displayed by the medical description content vector correction training model, and determining a target medical description content vector corresponding to the medical description content label under a preset type;
and updating medical user data acquired by a medical set by using the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content.
7. The system of claim 6, wherein the data intelligent processing end is specifically configured to:
displaying a user intelligent representation label at a medical treatment collection front end;
and responding to the input signal of the intelligent representation label of the user, and outputting a medical description content vector correction training model.
8. The system of claim 6, wherein the data intelligent processing end is specifically configured to:
acquiring abnormal target signals for executing at least two medical description content labels which belong to a preset type and are displayed by the vector correction training model;
and/or acquiring normal target signals for executing at least two medical description content labels which are not in a preset type and are displayed by the vector correction training model;
determining a target medical description content vector corresponding to the medical description content label updated to the preset type in response to the acquired screening signal; wherein the acquired screening signal comprises the abnormal target signal and/or the normal target signal;
the data intelligent processing terminal is specifically used for:
and for the medical user data acquired by the medical set, canceling the display of the medical user content corresponding to the medical description content label executing the abnormal target signal, and enhancing the display of the medical user content corresponding to the medical description content label executing the normal target signal.
9. The system of claim 6, wherein the data intelligent processing end is specifically configured to:
updating a medical acquisition matrix according to the determined target medical description content vector;
converting a first target medical description content vector newly loaded in an updated medical acquisition matrix and/or a second target medical description content vector which belongs to an unidentified state and is loaded in the medical acquisition matrix before updating into an identified state, and displaying medical user content corresponding to the corresponding target medical description content vector converted into the identified state in medical user data of a medical set;
acquiring a medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating, belongs to an identification state and is different from the target medical description content vector;
and canceling the identification state of the medical description content vector to be deleted so as to cancel the display of the medical user content corresponding to the medical description content vector to be deleted in the medical user data of the medical collection.
10. The system of claim 6, wherein the data intelligent processing end is specifically configured to:
dynamically displaying the medical description content labels of the simulated medical description content contained in the corresponding data set in the medical user data collected by the medical set;
the data intelligent processing terminal is specifically used for:
displaying a medical data compression range at the medical collection, wherein the medical data compression range includes at least two simulated interval boundaries determined based on a medical user protocol;
and dynamically displaying the spatial position change of the target simulated medical description content in the medical data compression range, wherein the target simulated medical description content refers to the simulated medical description content contained in the medical user content corresponding to the target medical description content vector.
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