CN113626688B - Intelligent medical data acquisition method and system based on software definition - Google Patents
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Abstract
According to the intelligent medical data acquisition method and system based on software definition, the medical description content vector correction training model is output to display the medical description content vectors in the medical users corresponding to the medical description content labels respectively, the medical description content labels can be freely determined, after the target medical description content vector is determined according to the screening signals of the medical description content labels, medical user content can be directly utilized to update medical user data and determine each medical user content, according to the medical user content, a user is not required to search the space positions of a plurality of corresponding simulation objects in the medical user, and compared with the mode that a plurality of simulation medical description contents to be checked need to be searched at present, the user content corresponding to the corresponding medical description content vector is sequentially acquired among the plurality of simulation medical description contents, so that the time spent for acquiring the user content of the plurality of simulation medical description contents is shortened.
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
Along with the continuous progress of information technology, medical data is continuously increased, and in the technology of traditional medical room data acquisition, the related medical data is likely to be difficult to acquire and time is wasted, so that the related medical data cannot be acquired timely, the related medical data is acquired through artificial intelligence, the efficiency of the related medical data acquisition can be effectively improved, and however, the technology for acquiring the medical data through artificial intelligence has some defects.
Disclosure of Invention
In view of the above, the application provides an intelligent medical data acquisition method and system based on software definition.
In a first aspect, there is provided a software-defined-based intelligent medical data acquisition method, 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 medical description content labels respectively correspond to medical description content vectors of different simulation medical description contents in a medical user;
Responding to the screening signals of the 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 the medical user data acquired by the medical collection by utilizing the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content.
Further, the obtaining the intelligent input signal of the user and outputting the medical description content vector correction training model comprises the following steps:
displaying a user intelligent representation tag at the front end of the medical collection;
and outputting a medical description content vector correction training model in response to an input signal to the user smart presentation tag.
Further, the determining, in response to the filtering signals of the plurality of medical description content tags displayed by the medical description content vector correction training model, a target medical description content vector corresponding to the medical description content tag under a preset type includes:
acquiring abnormal target signals which are displayed on the vector correction training model and are executed by at least two medical description content labels of a preset type;
And/or, acquiring normal target signals which are displayed by the vector correction training model and are executed on at least two medical description content labels of non-preset types;
responding to the acquired screening signals, and 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;
wherein updating medical user data collected by a 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 collection, canceling the display of the medical user content corresponding to the medical description content label for executing the abnormal target signal, and enhancing the display of the medical user content corresponding to the medical description content label for executing the normal target signal.
Further, 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, includes:
Updating a medical acquisition matrix by the determined target medical description content vector;
converting a first target medical description content vector newly loaded in the updated medical acquisition matrix and/or a second target medical description content vector belonging to an unidentified state loaded in the medical acquisition matrix before updating into an identification state, and displaying medical user contents corresponding to the corresponding target medical description content vector converted into the identification state in medical user data of a medical collection;
acquiring a medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating and belongs to an identification state and is different from the target medical description content vector;
canceling the identification state of the medical description content vector to be deleted so as to cancel the display of medical user content corresponding to the medical description content vector to be deleted in the medical user data of the medical set.
Further the method comprises the following steps:
dynamically displaying the medical description content labels of the simulated medical description contents contained in the corresponding data sets in the medical user data acquired by the medical sets;
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 simulation interval boundaries determined based on a medical user protocol;
and dynamically displaying the spatial position change of the target simulation medical description content in the medical data compression range, wherein the target simulation medical description content refers to the simulation medical description content contained in the medical user content corresponding to the target medical description content vector.
In a second aspect, a software-defined-based intelligent medical data acquisition system is provided, including a data acquisition device and a data intelligent processing end, where the data acquisition device is in communication connection with the data intelligent processing end, and the data intelligent processing end 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 medical description content labels respectively correspond to medical description content vectors of different simulation medical description contents in a medical user;
responding to the screening signals of the 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 the medical user data acquired by the medical collection by utilizing the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content.
Further, the data intelligent processing end is specifically configured to:
displaying a user intelligent representation tag at the front end of the medical collection;
and outputting a medical description content vector correction training model in response to an input signal to the user smart presentation tag.
Further, the data intelligent processing end is specifically configured to:
acquiring abnormal target signals which are displayed on the vector correction training model and are executed by at least two medical description content labels of a preset type;
and/or, acquiring normal target signals which are displayed by the vector correction training model and are executed on at least two medical description content labels of non-preset types;
responding to the acquired screening signals, and 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;
the data intelligent processing end is specifically configured to:
And for the medical user data acquired by the medical collection, canceling the display of the medical user content corresponding to the medical description content label for executing the abnormal target signal, and enhancing the display of the medical user content corresponding to the medical description content label for executing the normal target signal.
Further, the data intelligent processing end is specifically configured to:
updating a medical acquisition matrix by the determined target medical description content vector;
converting a first target medical description content vector newly loaded in the updated medical acquisition matrix and/or a second target medical description content vector belonging to an unidentified state loaded in the medical acquisition matrix before updating into an identification state, and displaying medical user contents corresponding to the corresponding target medical description content vector converted into the identification state in medical user data of a medical collection;
acquiring a medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating and belongs to an identification state and is different from the target medical description content vector;
canceling the identification state of the medical description content vector to be deleted so as to cancel the display of medical user content corresponding to the medical description content vector to be deleted in the medical user data of the medical set.
Further, the data intelligent processing end is specifically configured to:
dynamically displaying the medical description content labels of the simulated medical description contents contained in the corresponding data sets in the medical user data acquired by the medical sets;
the data intelligent processing end is specifically configured to:
displaying a medical data compression range at the medical collection, wherein the medical data compression range includes at least two simulation interval boundaries determined based on a medical user protocol;
and dynamically displaying the spatial position change of the target simulation medical description content in the medical data compression range, wherein the target simulation medical description content refers to the simulation medical description content contained in the medical user content corresponding to the target medical description content vector.
According to the intelligent medical data acquisition method and system based on the software definition, the user intelligent input signal is acquired in the medical collection, the medical description content vector correction training model is output to display a plurality of medical description content labels, the medical description content labels corresponding to different analog medical description contents in the medical users can be freely determined according to the medical description content vectors of the medical description contents corresponding to the medical description content vectors to be acquired, after the target medical description content vector to be displayed is determined according to the screening signal of the medical description content labels, the medical user data displayed in the medical collection can be updated by directly utilizing the medical user content corresponding to the medical description content labels, the medical user content corresponding to the medical collection is displayed, the medical user content corresponding to the screened medical description content vectors can be simultaneously checked according to personal requirements, the space positions of the corresponding analog medical description objects are not required to be searched in the medical users, compared with the medical description contents corresponding to the medical description contents needing to be checked at present, the medical description contents corresponding to the medical description vectors and the medical description contents needing to be searched in sequence among the analog description contents, and the medical description contents needing to be acquired, so that the medical description duration of the medical description contents corresponding to the user is shortened.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
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 a schematic 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 above technical solutions, the following detailed description of the technical solutions of the present application is made by using the accompanying drawings and specific embodiments, and it should be understood that the specific features of the embodiments and the embodiments of the present application are detailed descriptions of the technical solutions of the present application, and not limiting the technical solutions of the present application, and the technical features of the embodiments and the embodiments of the present application may be combined with each other without conflict.
Referring to fig. 1, a software-defined-based intelligent medical data acquisition method is shown, which may include the following steps 100-300.
Step 100, acquiring an intelligent input signal of a user, and outputting a medical description content vector correction training model.
The medical descriptor vector correction training model comprises a plurality of medical descriptor labels, wherein the medical descriptor labels respectively correspond to medical descriptor vectors of different simulated medical descriptor in a medical user.
Step 200, responding to the screening signals of the 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.
Illustratively, the target medical description content vector is used to characterize key features in the medical description content tag.
And 300, updating medical user data acquired by a medical collection by utilizing the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content.
Illustratively, updating the medical user data collected by the medical collection is used to characterize the collection of accurate medical user data.
It will be appreciated that when the technical solutions described in steps 100-300 are executed, a user intelligent input signal is performed on 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 labels, medical description content labels corresponding to different analog medical description contents in a medical user can be freely determined according to the medical description content labels corresponding to the medical description content vectors to be acquired, after a target medical description content vector to be displayed is determined in response to a screening signal for the medical description content labels, the medical user data displayed by the medical collection can be updated directly by utilizing the corresponding medical user content, the determined medical user content is displayed, the medical user content corresponding to each of the screened multiple medical description content vectors can be checked at the same time according to personal requirements, the user does not need to search the space positions of the corresponding multiple simulation objects in the medical user, and compared with the mode that the multiple simulation medical description contents needing to be checked are searched at present, the user content corresponding to the corresponding one medical description content vector is sequentially acquired among the multiple simulation medical description contents, so that the time spent for acquiring the user content of the multiple simulation medical description contents is shortened.
In an alternative embodiment, the inventor finds that when the intelligent input signal of the user is acquired, the input signal of the tag is inaccurate, so that it is difficult to accurately output the medical description content vector correction training model, and in order to improve the technical problem, the step of outputting the medical description content vector correction training model, which is described in step 100, by acquiring the intelligent input signal of the user, may specifically include the following technical schemes described in step q1 and step q 2.
And q1, displaying a user intelligent representation tag at the front end of the medical collection.
And q2, outputting a medical description content vector correction training model in response to the input signal of the user intelligent representation tag.
It can be understood that when the technical solutions described in the above steps q1 and q2 are executed, the inaccuracy problem of the input signal of the tag is improved when the intelligent input signal of the user is obtained, 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 screening signals of the plurality of medical description content tags displayed on the medical description content vector correction training model, there is a problem that the correction of the vector correction training model is inaccurate, 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 technical problem, the step of determining, in response to the screening signals of the plurality of medical description content tags displayed on the medical description content vector correction training model, the target medical description content vector corresponding to the medical description content tag under the preset type described in step 200 may specifically include the following technical scheme described in steps w 1-w 3.
And step w1, acquiring abnormal target signals which are displayed on the vector correction training model and are executed on at least two medical description content labels belonging to a preset type.
Step w2, and/or, acquiring normal target signals executed on at least two medical description content labels belonging to a non-preset type displayed by the vector correction training model.
Step w3, in response to the acquired screening signal, determining a target medical description content vector corresponding to the medical description content tag 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 the above steps w1 to w3 are executed, in response to the screening signals of the plurality of medical description content tags displayed by the medical description content vector correction training model, the problem of inaccuracy in correction of the vector correction training model is improved, so that the target medical description content vector corresponding to the medical description content tag 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 used, there is a problem that the display of the medical user content is inaccurate, so that it is difficult to accurately update the medical user data collected by the medical collection, and display the medical user content, and in order to improve the technical problem, the step of updating the medical user data collected by the medical collection and displaying the medical user content by using the medical user content corresponding to the determined target medical description content vector described in step 300 may specifically include the technical scheme described in the following step e 1.
And e1, canceling the display of medical user content corresponding to the medical description content label for executing the abnormal target signal and enhancing the display of medical user content corresponding to the medical description content label for executing the normal target signal for the medical user data acquired by the medical collection.
It can be understood that when the technical scheme described in the above step e1 is executed, the problem of inaccurate display of the medical user content is improved when the medical user content corresponding to the determined target medical description content vector is utilized, 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 used, the problem that the medical acquisition matrix is not accurate is solved, so that it is difficult to accurately update the medical user data acquired by the medical collection, the medical user content is displayed, in order to improve the technical problem, the step of updating the medical user data acquired by the medical collection and displaying the medical user content by using the medical user content corresponding to the determined target medical description content vector described in step 300 specifically may include the following technical scheme described in steps r 1-r 4.
And r1, updating a medical acquisition matrix by the determined target medical description content vector.
And r2, converting a first target medical description content vector newly loaded in the updated medical acquisition matrix and/or a second target medical description content vector belonging to an unidentified state loaded in the medical acquisition matrix before updating into an identification state, and displaying medical user contents corresponding to the corresponding target medical description content vector converted into the identification state in medical user data of a medical collection.
And r3, acquiring the medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating and belongs to an 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 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 scheme described in the steps r1 to r4 is executed, the problem of inaccurate updating of the medical acquisition matrix is solved when the medical user content corresponding to the determined target medical description content vector is used, 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, the technical solution described in the following step t1 may also be included.
And 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 acquired by the medical set.
It will be appreciated that the accuracy of the medical description content label is improved by dynamic display when the technical scheme described in step t1 is performed.
Based on the above, the technical solutions 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 simulated interval boundaries determined based on a medical user protocol.
And step y2, dynamically displaying the spatial position change of the target simulation medical description content in the medical data compression range.
For example, 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
It will be appreciated that in performing the technical solutions described in step y1 and step y2 above, the accuracy of dynamically displaying spatial position changes of the target simulated medical description content is improved by displaying the medical data compression range.
Based on the above, the technical solution described in the following step a1 may also be included.
And a step a1 of determining that the number of the target medical description content vectors is a plurality of, and obtaining the medical description content space position display type corresponding to each of the plurality of the target medical description content vectors.
It will be understood that, when the technical solution described in the above step a1 is executed, by a plurality of target medical description content vectors, the medical description content spatial position display type corresponding to each of the plurality of target medical description content vectors can be accurately obtained.
In one possible embodiment, the inventor finds that, in the medical data compression range, when the spatial position of the target analog medical description content is dynamically displayed, there are different target medical description content vectors, so that it is difficult to accurately dynamically display the spatial position change of the target analog medical description content, and in order to improve the technical problem, the step of dynamically displaying the spatial position change of the target analog medical description content in the medical data compression range described in the step y2 may specifically include the technical scheme described in the following step y 21.
And step 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, and presenting the corresponding medical description content spatial position display types.
It can be understood that when the technical solution described in the above step y21 is executed, different target medical description content vectors are improved when the spatial position of the target analog medical description content is dynamically displayed in the medical data compression range, so that the spatial position change of the target analog medical description content can be accurately and dynamically displayed.
Based on the above, the technical solutions described in the following step d1 and step d2 may also be included.
And d1, responding to a screening signal of any simulation interval boundary of the medical data compression range, and determining user content to be acquired corresponding to the screened simulation interval boundary.
And d2, updating the medical user data acquired by the medical collection into the user content acquisition to be acquired.
It can be understood that when the technical schemes described in the above steps d1 and d2 are executed, the accuracy of updating to the acquisition of the user content to be acquired is improved by accurately determining the user content to be acquired corresponding to the screened boundary of the simulation interval.
On the basis of the foregoing, please refer to fig. 2 in combination, there is provided a software-defined-based intelligent medical data acquisition device 200, applied to an intelligent data processing terminal, the device comprising:
an input signal obtaining module 210, configured to obtain an intelligent input signal of a user, and output a medical description content vector correction training model, where the medical description content vector correction 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 analog medical description contents in the medical user;
a description content determining module 220, configured to determine a target medical description content vector corresponding to the medical description content tag under a preset type in response to the screening signals of the plurality of medical description content tags displayed on the medical description content vector correction training model;
the user data updating model 230 is configured to update 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 display the medical user content.
On the above basis, referring to fig. 3 in combination, a software-defined based intelligent medical data acquisition system 300 is shown, comprising a processor 310 and a memory 320 in communication with each other, the processor 310 being configured to read and execute a computer program from the memory 320 to implement the method described above.
On the basis of the above, there is also provided a computer readable storage medium on which a computer program stored which, when run, implements the above method.
In summary, based on the above scheme, the user intelligent input signal is performed on the medical collection, the user intelligent input signal is obtained, the medical description content vector correction training model is output, so as to display a plurality of medical description content labels, according to the medical description content vectors of different analog medical description contents in the medical users, the medical description content labels 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 screening signal of the medical description content labels, the medical user content corresponding to the target medical description content vector to be displayed can be directly utilized, the medical user data displayed by the medical collection is updated, each medical user content determined is displayed, the medical description content corresponding to each medical user content selected by the medical collection can be simultaneously checked according to personal requirements, the space position of the corresponding analog medical description content corresponding to the medical user is not required to be searched in the medical user, the medical description content corresponding to the medical description vector corresponding to be checked is required to be searched, and the medical description content corresponding to the analog to be acquired in the medical description content is sequentially, and the duration of the medical description content corresponding to the medical description content of the user is shortened.
It should be appreciated that the systems and modules thereof 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 then be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or special purpose design 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 as provided on a carrier medium such as a magnetic disk, 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 of the present application and its modules may be implemented not only with hardware circuitry such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also with software executed by various types of processors, for example, and with a combination of the above hardware circuitry and software (e.g., firmware).
It should be noted that, the advantages that may be generated by different embodiments may be different, and in different embodiments, the advantages that may be generated may be any one or a combination of several of the above, or any other possible advantages that may be obtained.
While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing detailed disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements and adaptations of the application may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be suggested within the present disclosure, and therefore, such modifications, improvements, and adaptations are intended to be within the spirit and scope of the exemplary embodiments of the present disclosure.
Meanwhile, the present application uses specific words to describe embodiments of the present application. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the application. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the application may be combined as suitable.
Furthermore, those skilled in the art will appreciate that the various aspects of the application are illustrated and described in the context of a number of patentable categories or circumstances, including any novel and useful procedures, machines, products, or materials, or any novel and useful modifications thereof. Accordingly, aspects of the application may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.) or by a combination of hardware and software. The above hardware or software may be referred to as a "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the application may take the form of a computer product, comprising computer-readable program code, embodied in one or more computer-readable media.
The computer storage medium may contain a propagated data signal with the computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take on a variety of forms, including electro-magnetic, optical, etc., or any suitable combination thereof. 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 through any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or a combination of any of the foregoing.
The computer program code necessary for operation of 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, etc., a conventional programming language such as C language, visual Basic, fortran 2003, perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, ruby and Groovy, or other programming languages, etc. The program code may execute entirely on the user's computer or 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 form of network, 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 the use of services such as software as a service (SaaS) in a cloud computing environment.
Furthermore, the order in which the elements and sequences are presented, the use of numerical letters, or other designations are used in the application is not intended to limit the sequence of the processes and methods unless specifically recited in the claims. While certain presently useful inventive embodiments have been discussed in the foregoing disclosure, by way of example, it is to be understood that such details are merely illustrative 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 included within the spirit and scope of the embodiments of the application. For example, while the system components described above may be implemented by hardware devices, they may also be implemented solely by software solutions, such as installing the described system on an existing server or mobile device.
Similarly, it should be noted that in order to simplify the description of the present disclosure and thereby aid in understanding one or more inventive embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof. This method of disclosure, however, is not intended to imply that more features than are required by the subject application. Indeed, less than all of the features of a single embodiment disclosed above.
In some embodiments, numbers describing the components, number of attributes are used, it being understood that such numbers being used in the description of embodiments are modified in some examples by the modifier "about," approximately, "or" substantially. Unless otherwise indicated, "about," "approximately," or "substantially" indicate that the numbers allow for adaptive variation. Accordingly, in some embodiments, numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and employ a method for preserving the general number of digits. Although the numerical ranges and parameters set forth herein are approximations in some embodiments for use in determining the breadth of the range, in particular embodiments, the numerical values set forth herein are as precisely as possible.
Each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited herein is hereby incorporated by reference in its entirety. Except for the application history file that is inconsistent or conflicting with this disclosure, the file (currently or later attached to this disclosure) that limits the broadest scope of the claims of this disclosure is also excluded. It is noted that the description, definition, and/or use of the term in the appended claims controls the description, definition, and/or use of the term in this application if there is a discrepancy or conflict between the description, definition, and/or use of the term in the appended claims.
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 application. Thus, by way of example, and not limitation, alternative configurations of embodiments of the application may be considered in keeping with the teachings of the application. Accordingly, the embodiments of the present application are not limited to the embodiments explicitly described and depicted herein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (6)
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 medical description content labels respectively correspond to medical description content vectors of different simulation medical description contents in a medical user;
responding to the screening signals of the 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;
updating medical user data acquired by a medical collection by utilizing medical user content corresponding to the determined target medical description content vector, and displaying the medical user content;
the determining, in response to the screening signals of the plurality of medical description content tags displayed by the medical description content vector correction training model, a target medical description content vector corresponding to the medical description content tag belonging to a preset type includes:
Acquiring abnormal target signals which are displayed on the vector correction training model and are executed by at least two medical description content labels of a preset type;
and/or, acquiring normal target signals which are displayed by the vector correction training model and are executed on at least two medical description content labels of non-preset types;
responding to the acquired screening signals, and 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;
wherein updating medical user data collected by a medical collection by using the medical user content corresponding to the determined target medical description content vector, and displaying the medical user content, comprises:
for the medical user data collected by the medical collection, canceling the display of medical user content corresponding to the medical description content label for executing the abnormal target signal, and enhancing the display of medical user content corresponding to the medical description content label for executing the normal target signal;
the updating of 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 the displaying of the medical user content, comprises the following steps:
Updating a medical acquisition matrix by the determined target medical description content vector;
converting a first target medical description content vector newly loaded in the updated medical acquisition matrix and/or a second target medical description content vector belonging to an unidentified state loaded in the medical acquisition matrix before updating into an identification state, and displaying medical user contents corresponding to the corresponding target medical description content vector converted into the identification state in medical user data of a medical collection;
acquiring a medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating and belongs to an identification state and is different from the target medical description content vector;
canceling the identification state of the medical description content vector to be deleted so as to cancel the display of medical user content corresponding to the medical description content vector to be deleted in the medical user data of the medical set.
2. The method of claim 1, wherein the acquiring the user-intelligent input signal, outputting the medical description vector modification training model, comprises:
displaying a user intelligent representation tag at the front end of the medical collection;
And outputting a medical description content vector correction training model in response to an input signal to the user smart presentation tag.
3. The method according to claim 1, wherein the method further comprises:
dynamically displaying the medical description content labels of the simulated medical description contents contained in the corresponding data sets in the medical user data acquired by the medical sets;
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 simulation interval boundaries determined based on a medical user protocol;
and dynamically displaying the spatial position change of the target simulation medical description content in the medical data compression range, wherein the target simulation medical description content refers to the simulation medical description content contained in the medical user content corresponding to the target medical description content vector.
4. The intelligent medical data acquisition system based on software definition is characterized by comprising data acquisition equipment and a data intelligent processing end, wherein the data acquisition equipment is in communication connection with the data intelligent processing end, and the data intelligent processing end 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 medical description content labels respectively correspond to medical description content vectors of different simulation medical description contents in a medical user;
responding to the screening signals of the 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;
updating medical user data acquired by a medical collection by utilizing medical user content corresponding to the determined target medical description content vector, and displaying the medical user content;
the data intelligent processing end is specifically used for:
acquiring abnormal target signals which are displayed on the vector correction training model and are executed by at least two medical description content labels of a preset type;
and/or, acquiring normal target signals which are displayed by the vector correction training model and are executed on at least two medical description content labels of non-preset types;
Responding to the acquired screening signals, and 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;
the data intelligent processing end is specifically configured to:
for the medical user data collected by the medical collection, canceling the display of medical user content corresponding to the medical description content label for executing the abnormal target signal, and enhancing the display of medical user content corresponding to the medical description content label for executing the normal target signal;
the data intelligent processing end is specifically used for:
updating a medical acquisition matrix by the determined target medical description content vector;
converting a first target medical description content vector newly loaded in the updated medical acquisition matrix and/or a second target medical description content vector belonging to an unidentified state loaded in the medical acquisition matrix before updating into an identification state, and displaying medical user contents corresponding to the corresponding target medical description content vector converted into the identification state in medical user data of a medical collection;
Acquiring a medical description content vector to be deleted, which is loaded by the medical acquisition matrix before updating and belongs to an identification state and is different from the target medical description content vector;
canceling the identification state of the medical description content vector to be deleted so as to cancel the display of medical user content corresponding to the medical description content vector to be deleted in the medical user data of the medical set.
5. The system of claim 4, wherein the data intelligent processing terminal is specifically configured to:
displaying a user intelligent representation tag at the front end of the medical collection;
and outputting a medical description content vector correction training model in response to an input signal to the user smart presentation tag.
6. The system of claim 4, wherein the data intelligent processing terminal is specifically configured to:
dynamically displaying the medical description content labels of the simulated medical description contents contained in the corresponding data sets in the medical user data acquired by the medical sets;
the data intelligent processing end is specifically configured to:
displaying a medical data compression range at the medical collection, wherein the medical data compression range includes at least two simulation interval boundaries determined based on a medical user protocol;
And dynamically displaying the spatial position change of the target simulation medical description content in the medical data compression range, wherein the target simulation medical description content refers to the simulation medical description content contained in the medical user content corresponding to the target medical description content vector.
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