CN113645604A - Intelligent medical ward help calling method and system - Google Patents
Intelligent medical ward help calling method and system Download PDFInfo
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- CN113645604A CN113645604A CN202110847539.0A CN202110847539A CN113645604A CN 113645604 A CN113645604 A CN 113645604A CN 202110847539 A CN202110847539 A CN 202110847539A CN 113645604 A CN113645604 A CN 113645604A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/90—Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/56—Allocation or scheduling criteria for wireless resources based on priority criteria
- H04W72/566—Allocation or scheduling criteria for wireless resources based on priority criteria of the information or information source or recipient
- H04W72/569—Allocation or scheduling criteria for wireless resources based on priority criteria of the information or information source or recipient of the traffic information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W76/00—Connection management
- H04W76/50—Connection management for emergency connections
Abstract
According to the ward distress method and system based on intelligent medical treatment, important signal nodes are screened based on description characteristics and description characteristics of the important signal nodes, the screened important signal nodes and the important signal nodes form a target association set, and whether the content of a signal to be processed and the content of a sample signal are the same is determined based on each important signal node in the target association set. Due to the fact that the important signal nodes are screened, the probability that two important signal nodes of the important signal nodes do not actually belong to the same important signal node is greatly reduced, and then when the signal content is identified based on the target association set, the comparison result of the two important signal nodes which do not actually belong to the same important signal node can be reduced or even avoided as the basis for judging the signal content identification result, and therefore compared with the method in the prior art, the method can obviously improve the accuracy of signal content identification.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a ward distress calling method and system based on intelligent medical treatment.
Background
With the continuous development of information technology, the communication technology is applied to clinical medicine, so that a patient can quickly inform relevant medical personnel when encountering an emergency, however, the condition of information disorder may exist in the transmission process of the distress call data, so that the distress call data cannot be accurately and completely transmitted to the relevant medical personnel, and thus, emergency measures cannot be timely carried out on the patient.
Disclosure of Invention
In view of the above, the present application provides a ward distress call method and system based on smart medical treatment.
In a first aspect, a ward distress method based on smart medical treatment is provided, which includes:
acquiring a target medical response signal, wherein the target medical response signal comprises identification data of the content of a signal to be processed;
according to the description characteristics of the important signal nodes of the target medical response signal and the description characteristics of the important signal nodes of the sample medical response signal, screening the important signal nodes in the target medical response signal to obtain a target association set, wherein the target association set comprises a plurality of important signal nodes, each important signal node comprises one important signal node in the screened target medical response signal and one important signal node in the sample medical response signal associated with the description characteristics of the important signal node, and the sample medical response signal comprises identification data of sample signal content;
and obtaining a signal content identification result according to the important signal node in the target association set, wherein the signal content identification result is used for indicating whether the signal content to be processed and the sample signal content are the same signal content.
Further, the screening the important signal nodes in the target medical response signal according to the description features of the important signal nodes of the target medical response signal and the description features of the important signal nodes of the sample medical response signal to obtain a target association set includes:
screening important signal nodes of the target medical response signal according to the description characteristics of the important signal nodes of the target medical response signal and the attributes of the description characteristics of the important signal nodes of the sample medical response signal to obtain a first association set, wherein the first association set comprises a plurality of important signal nodes, each important signal node comprises the important signal node of the target medical response signal after screening according to the attributes of the description characteristics and the important signal node in the sample medical response signal associated with the important signal node of the target medical response signal after screening;
screening important signal nodes in the first association set according to signal errors and signal correction among the important signal nodes of the important signal nodes in the first association set to obtain a second association set;
and screening the second association set according to the attribute of the description characteristics of the important signal nodes in the second association set to obtain the target association set.
Further, the screening, according to the attributes of the description features of the important signal nodes of the target medical response signal and the description features of the important signal nodes of the sample medical response signal, the important signal nodes of the target medical response signal to obtain a first association set includes:
determining a second important signal node ranked first and a third important signal node ranked second according to the description feature relevance of the first important signal node in the target medical response signal, wherein the second important signal node and the third important signal node are important signal nodes in the sample medical response signal;
determining whether to screen the first important signal node according to the description features of the first important signal node and the attributes of the description features of the second important signal node, and the attributes of the description features of the second important signal node and the attributes of the description features of the third important signal node;
and if the first important signal node is determined not to be screened, using the important signal node formed by the first important signal node and the second important signal node as one important signal node in the first association set.
Further, the screening the important signal nodes in the first association set according to the signal error and the signal correction between the important signal nodes of the important signal nodes in the first association set to obtain a second association set includes:
counting signal errors and signal corrections among important signal nodes of all the important signal nodes in the first association set to obtain a first matrix;
taking the important signal node in the error vector with the largest value in the first matrix as the important signal node in the second correlation set;
wherein the screening the second association set according to the attribute of the description feature of the important signal node in the second association set to obtain the target association set includes:
if two important signal nodes in the second association set both include a fourth important signal node, and the fourth important signal node is an important signal node in the sample medical response signal, the important signal node with the small description feature attribute of the two important signal nodes where the fourth important signal node is located is taken as the important signal node in the target association set, wherein the description feature attribute of the important signal node is the feature attribute of the two important signal nodes in the important signal nodes.
Further, the obtaining a signal content identification result according to the important signal node in the target association set includes:
and obtaining the signal content identification result according to the description characteristic attribute of each important signal node in the target association set.
The second aspect provides a ward distress system based on wisdom medical treatment, including data acquisition end and data processing terminal, the data acquisition end with data processing terminal communication connection, data processing terminal specifically is used for:
acquiring a target medical response signal, wherein the target medical response signal comprises identification data of the content of a signal to be processed;
according to the description characteristics of the important signal nodes of the target medical response signal and the description characteristics of the important signal nodes of the sample medical response signal, screening the important signal nodes in the target medical response signal to obtain a target association set, wherein the target association set comprises a plurality of important signal nodes, each important signal node comprises one important signal node in the screened target medical response signal and one important signal node in the sample medical response signal associated with the description characteristics of the important signal node, and the sample medical response signal comprises identification data of sample signal content;
and obtaining a signal content identification result according to the important signal node in the target association set, wherein the signal content identification result is used for indicating whether the signal content to be processed and the sample signal content are the same signal content.
Further, the data processing terminal is specifically configured to:
screening important signal nodes of the target medical response signal according to the description characteristics of the important signal nodes of the target medical response signal and the attributes of the description characteristics of the important signal nodes of the sample medical response signal to obtain a first association set, wherein the first association set comprises a plurality of important signal nodes, each important signal node comprises the important signal node of the target medical response signal after screening according to the attributes of the description characteristics and the important signal node in the sample medical response signal associated with the important signal node of the target medical response signal after screening;
screening important signal nodes in the first association set according to signal errors and signal correction among the important signal nodes of the important signal nodes in the first association set to obtain a second association set;
and screening the second association set according to the attribute of the description characteristics of the important signal nodes in the second association set to obtain the target association set.
Further, the data processing terminal is specifically configured to:
determining a second important signal node ranked first and a third important signal node ranked second according to the description feature relevance of the first important signal node in the target medical response signal, wherein the second important signal node and the third important signal node are important signal nodes in the sample medical response signal;
determining whether to screen the first important signal node according to the description features of the first important signal node and the attributes of the description features of the second important signal node, and the attributes of the description features of the second important signal node and the attributes of the description features of the third important signal node;
and if the first important signal node is determined not to be screened, using the important signal node formed by the first important signal node and the second important signal node as one important signal node in the first association set.
Further, the data processing terminal is specifically configured to:
counting signal errors and signal corrections among important signal nodes of all the important signal nodes in the first association set to obtain a first matrix;
taking the important signal node in the error vector with the largest value in the first matrix as the important signal node in the second correlation set;
wherein the data processing terminal is specifically configured to:
if two important signal nodes in the second association set both include a fourth important signal node, and the fourth important signal node is an important signal node in the sample medical response signal, the important signal node with the small description feature attribute of the two important signal nodes where the fourth important signal node is located is taken as the important signal node in the target association set, wherein the description feature attribute of the important signal node is the feature attribute of the two important signal nodes in the important signal nodes.
Further, the data processing terminal is specifically configured to:
and obtaining the signal content identification result according to the description characteristic attribute of each important signal node in the target association set.
According to the ward distress method and system based on intelligent medical treatment, after a target medical response signal containing to-be-processed signal content is acquired, important signal nodes in the target medical response signal are screened based on the description characteristics of the important signal nodes of the target medical response signal and the description characteristics of the important signal nodes of a sample medical response signal, the screened important signal nodes of the target medical response signal and the important signal nodes in the sample medical response signal related to the important signal nodes form a target related set, and whether the to-be-processed signal content and the sample signal content in the sample medical response signal are the same signal content or not is determined based on all the important signal nodes in the target related set. Because the important signal nodes of the target medical response signal are screened, the probability that two important signal nodes of the important signal nodes in the target association set do not actually belong to the same important signal node is greatly reduced, and further, when the signal content is identified based on the target association set, the comparison result of the two important signal nodes which do not actually belong to the same important signal node can be reduced or even avoided as the basis for judging the signal content identification result, so that compared with the method in the prior art, the accuracy of signal content identification can be obviously improved. Even in the case where the signal content in the target medical response signal is unstable, a higher signal content recognition accuracy can be obtained using the present embodiment.
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 a ward distress call method based on smart medical treatment according to an embodiment of the present application.
Fig. 2 is a block diagram of a ward distress call device based on smart medical treatment according to an embodiment of the present application.
Fig. 3 is an architecture diagram of a ward distress system based on smart medical treatment 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, a ward distress call method based on smart medical treatment is shown, which may include the following steps 100-300.
Step 100, acquiring a target medical response signal, wherein the target medical response signal comprises identification data of the content of a signal to be processed.
It can be understood that, when the technical solutions described in steps 100 to 300 are performed, after a target medical response signal including a signal content to be processed is acquired, important signal nodes in the target medical response signal are screened based on the description features of the important signal nodes of the target medical response signal and the description features of the important signal nodes of the sample medical response signal, the screened important signal nodes of the target medical response signal and the important signal nodes in the sample medical response signal associated with the important signal nodes form a target association set, and then based on each important signal node in the target association set, it is determined whether the signal content to be processed and the sample signal content in the sample medical response signal are the same signal content. Because the important signal nodes of the target medical response signal are screened, the probability that two important signal nodes of the important signal nodes in the target association set do not actually belong to the same important signal node is greatly reduced, and further, when the signal content is identified based on the target association set, the comparison result of the two important signal nodes which do not actually belong to the same important signal node can be reduced or even avoided as the basis for judging the signal content identification result, so that compared with the method in the prior art, the accuracy of signal content identification can be obviously improved. Even in the case where the signal content in the target medical response signal is unstable, a higher signal content recognition accuracy can be obtained using the present embodiment.
In an alternative embodiment, the inventors found that, when the important signal nodes in the target medical response signal are screened according to the description characteristics of the important signal nodes of the target medical response signal and the description characteristics of the important signal nodes of the sample medical response signal, there is a problem that the screening is inaccurate, so that it is difficult to accurately obtain the target association set, and in order to improve the above technical problem, the step of screening the important signal nodes in the target medical response signal according to the description characteristics of the important signal nodes of the target medical response signal and the description characteristics of the important signal nodes of the sample medical response signal, which is described in step 200, and obtaining the target association set may specifically include the technical solutions described in steps 210 to 230 below.
And 230, screening the second association set according to the attribute of the description feature of the important signal node in the second association set to obtain the target association set.
It can be understood that, when the technical solutions described in steps 210 to 230 are performed, when the important signal nodes in the target medical response signal are screened according to the description features of the important signal nodes of the target medical response signal and the description features of the important signal nodes of the sample medical response signal, the problem of inaccurate screening is improved, so that the target association set can be accurately obtained.
In an alternative embodiment, the inventor finds that, when the important signal nodes of the target medical response signal are screened according to the description characteristics of the important signal nodes of the target medical response signal and the description characteristics of the important signal nodes of the sample medical response signal, there is a problem that the description characteristics are not accurate, so that it is difficult to accurately obtain the first association set, and in order to improve the above technical problem, the step of screening the important signal nodes of the target medical response signal according to the description characteristics of the important signal nodes of the target medical response signal and the description characteristics of the important signal nodes of the sample medical response signal, which is described in step 210, so as to obtain the first association set may specifically include the technical solutions described in steps 211 to 213 below.
Step 211, determining a second important signal node ranked first and a third important signal node ranked second according to the description feature association degree of the first important signal node in the target medical response signal, wherein the second important signal node and the third important signal node are important signal nodes in the sample medical response signal.
Step 212, determining whether to screen the first important signal node according to the description features of the first important signal node and the attributes of the description features of the second important signal node, and the attributes of the description features of the second important signal node and the attributes of the description features of the third important signal node.
Step 213, if it is determined that the first important signal node is not to be filtered, using an important signal node composed of the first important signal node and the second important signal node as an important signal node in the first association set.
It can be understood that, when the technical solutions described in steps 211 to 213 are executed, the problem of inaccuracy of the attributes of the description features is improved when the important signal nodes of the target medical response signal are screened according to the attributes of the description features of the important signal nodes of the target medical response signal and the description features of the important signal nodes of the sample medical response signal, so that the first association set can be accurately obtained.
In an alternative embodiment, the inventor finds that, when filtering important signal nodes in the first association set according to signal errors and signal corrections between the important signal nodes of the important signal nodes in the first association set, there is a problem that the corrections are inaccurate, so that it is difficult to accurately obtain the second association set, and in order to improve the above technical problem, the step of filtering important signal nodes in the first association set according to signal errors and signal corrections between the important signal nodes of the important signal nodes in the first association set, which is described in step 220, to obtain the second association set may specifically include the technical solutions described in the following steps 221 and 222.
Step 221, counting signal errors and signal corrections between the important signal nodes of each important signal node in the first association set to obtain a first matrix.
Step 222, using the important signal node in the error vector with the largest value in the first matrix as the important signal node in the second correlation set.
It can be understood that, when the technical solutions described in the above steps 221 and 222 are performed, when the important signal nodes in the first association set are screened according to the signal error and the signal correction between the important signal nodes of the important signal nodes in the first association set, the problem of inaccurate correction is improved, so that the second association set can be accurately obtained.
In an alternative embodiment, the inventors found that, when the second association set is filtered according to the attribute of the description feature of the important signal node in the second association set, there is a problem that two important signal nodes are not accurate, so that it is difficult to accurately obtain the target association set, and in order to improve the above technical problem, the step of filtering the second association set according to the attribute of the description feature of the important signal node in the second association set, which is described in step 230, may specifically include the technical solution described in step 231 below.
Step 231, if two important signal nodes in the second association set both include a fourth important signal node, and the fourth important signal node is an important signal node in the sample medical response signal, taking an important signal node with a small description feature attribute of the two important signal nodes where the fourth important signal node is located as an important signal node in the target association set, where the description feature attribute of the important signal node is an attribute of the description feature of the two important signal nodes in the important signal nodes.
It can be understood that, when the technical solution described in the above step 231 is executed, two important signal nodes are not accurate when the second association set is screened according to the attribute of the description feature of the important signal node in the second association set, so that it is difficult to accurately obtain the target association set.
In an alternative embodiment, the inventor finds that, when an important signal node in the target association set is associated, there is a problem that the description characteristic attribute of each important signal node is not reliable, so that it is difficult to reliably obtain a signal content identification result, and in order to improve the above technical problem, the step of obtaining a signal content identification result according to an important signal node in the target association set, which is described in step 300, may specifically include the technical solution described in step q1 below.
And q1, obtaining the signal content identification result according to the description characteristic attributes of each important signal node in the target association set.
It can be understood that, when the technical solution described in step q1 is executed, according to the important signal nodes in the target association set, the problem that the description feature attributes of each important signal node are not reliable is solved, so that the signal content identification result can be reliably obtained.
In a possible embodiment, the inventor finds that, in accordance with the description characteristic attribute of each important signal node in the target association set, there is a problem of difference, so that it is difficult to accurately obtain the signal content identification result, and in order to improve the above technical problem, the step of obtaining the signal content identification result according to the description characteristic attribute of each important signal node in the target association set, which is described in step q1, may specifically include the technical solutions described in the following step q 11-step q 13.
And q11, determining the difference between the description characteristic attribute of each important signal node in the target association set and the attribute set in advance.
And q12, integrating the differences corresponding to the important signal nodes in the target association set to obtain an integrated result.
And q13, if the integration result meets a preset index, determining that the signal content identification result is that the signal content to be processed and the sample signal content are the same signal content.
It can be understood that, when the technical solutions described in the above steps q 11-q 13 are executed, the problem of difference is avoided when describing characteristic attributes of each important signal node in the target association set, so that the signal content identification result can be accurately obtained.
On the basis, please refer to fig. 2 in combination, a ward distress call device 200 based on smart medical treatment is provided, which is applied to a data processing terminal, and comprises:
a signal acquisition module 210, configured to acquire a target medical response signal, where the target medical response signal includes identification data of a signal content to be processed;
a signal screening module 220, configured to screen important signal nodes in the target medical response signal according to description features of the important signal nodes of the target medical response signal and description features of the important signal nodes of the sample medical response signal, and obtain a target association set, where the target association set includes a plurality of important signal nodes, each important signal node includes one important signal node in the screened target medical response signal and one important signal node in the sample medical response signal associated with the description feature of the one important signal node, and the sample medical response signal includes identification data of sample signal content;
a result identifying module 230, configured to obtain a signal content identifying result according to the important signal node in the target association set, where the signal content identifying result is used to indicate whether the signal content to be processed and the sample signal content are the same signal content.
On the basis of the above, please refer to fig. 3 in combination, which shows a smart medical ward distress call system 300, 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 scheme, after a target medical response signal including a content of a signal to be processed is acquired, important signal nodes in the target medical response signal are screened based on the description features of the important signal nodes of the target medical response signal and the description features of the important signal nodes of the sample medical response signal, the screened important signal nodes of the target medical response signal and the important signal nodes in the sample medical response signal associated with the important signal nodes form a target association set, and then based on each important signal node in the target association set, it is determined whether the content of the signal to be processed and the content of the sample signal in the sample medical response signal are the same signal content. Because the important signal nodes of the target medical response signal are screened, the probability that two important signal nodes of the important signal nodes in the target association set do not actually belong to the same important signal node is greatly reduced, and further, when the signal content is identified based on the target association set, the comparison result of the two important signal nodes which do not actually belong to the same important signal node can be reduced or even avoided as the basis for judging the signal content identification result, so that compared with the method in the prior art, the accuracy of signal content identification can be obviously improved. Even in the case where the signal content in the target medical response signal is unstable, a higher signal content recognition accuracy can be obtained using the present embodiment.
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. A ward distress method based on intelligent medical treatment is characterized by comprising the following steps:
acquiring a target medical response signal, wherein the target medical response signal comprises identification data of the content of a signal to be processed;
according to the description characteristics of the important signal nodes of the target medical response signal and the description characteristics of the important signal nodes of the sample medical response signal, screening the important signal nodes in the target medical response signal to obtain a target association set, wherein the target association set comprises a plurality of important signal nodes, each important signal node comprises one important signal node in the screened target medical response signal and one important signal node in the sample medical response signal associated with the description characteristics of the important signal node, and the sample medical response signal comprises identification data of sample signal content;
and obtaining a signal content identification result according to the important signal node in the target association set, wherein the signal content identification result is used for indicating whether the signal content to be processed and the sample signal content are the same signal content.
2. The method according to claim 1, wherein the screening the important signal nodes in the target medical response signal according to the description features of the important signal nodes of the target medical response signal and the description features of the important signal nodes of the sample medical response signal, and obtaining a target association set comprises:
screening important signal nodes of the target medical response signal according to the description characteristics of the important signal nodes of the target medical response signal and the attributes of the description characteristics of the important signal nodes of the sample medical response signal to obtain a first association set, wherein the first association set comprises a plurality of important signal nodes, each important signal node comprises the important signal node of the target medical response signal after screening according to the attributes of the description characteristics and the important signal node in the sample medical response signal associated with the important signal node of the target medical response signal after screening;
screening important signal nodes in the first association set according to signal errors and signal correction among the important signal nodes of the important signal nodes in the first association set to obtain a second association set;
and screening the second association set according to the attribute of the description characteristics of the important signal nodes in the second association set to obtain the target association set.
3. The method according to claim 2, wherein the screening the important signal nodes of the target medical response signal according to the attributes of the descriptive characteristics of the important signal nodes of the target medical response signal and the descriptive characteristics of the important signal nodes of the sample medical response signal to obtain a first association set comprises:
determining a second important signal node ranked first and a third important signal node ranked second according to the description feature relevance of the first important signal node in the target medical response signal, wherein the second important signal node and the third important signal node are important signal nodes in the sample medical response signal;
determining whether to screen the first important signal node according to the description features of the first important signal node and the attributes of the description features of the second important signal node, and the attributes of the description features of the second important signal node and the attributes of the description features of the third important signal node;
and if the first important signal node is determined not to be screened, using the important signal node formed by the first important signal node and the second important signal node as one important signal node in the first association set.
4. The method of claim 2, wherein the screening the important signal nodes in the first association set according to the signal error and the signal correction between the important signal nodes in the first association set to obtain a second association set comprises:
counting signal errors and signal corrections among important signal nodes of all the important signal nodes in the first association set to obtain a first matrix;
taking the important signal node in the error vector with the largest value in the first matrix as the important signal node in the second correlation set;
wherein the screening the second association set according to the attribute of the description feature of the important signal node in the second association set to obtain the target association set includes:
if two important signal nodes in the second association set both include a fourth important signal node, and the fourth important signal node is an important signal node in the sample medical response signal, the important signal node with the small description feature attribute of the two important signal nodes where the fourth important signal node is located is taken as the important signal node in the target association set, wherein the description feature attribute of the important signal node is the feature attribute of the two important signal nodes in the important signal nodes.
5. The method according to any one of claims 1 to 4, wherein the obtaining a signal content identification result according to the important signal node in the target association set comprises:
and obtaining the signal content identification result according to the description characteristic attribute of each important signal node in the target association set.
6. The utility model provides a ward distress system based on wisdom medical treatment which characterized in that, includes data acquisition end and data processing terminal, the data acquisition end with data processing terminal communication connection, data processing terminal specifically is used for:
acquiring a target medical response signal, wherein the target medical response signal comprises identification data of the content of a signal to be processed;
according to the description characteristics of the important signal nodes of the target medical response signal and the description characteristics of the important signal nodes of the sample medical response signal, screening the important signal nodes in the target medical response signal to obtain a target association set, wherein the target association set comprises a plurality of important signal nodes, each important signal node comprises one important signal node in the screened target medical response signal and one important signal node in the sample medical response signal associated with the description characteristics of the important signal node, and the sample medical response signal comprises identification data of sample signal content;
and obtaining a signal content identification result according to the important signal node in the target association set, wherein the signal content identification result is used for indicating whether the signal content to be processed and the sample signal content are the same signal content.
7. The system of claim 6, wherein the data processing terminal is specifically configured to:
screening important signal nodes of the target medical response signal according to the description characteristics of the important signal nodes of the target medical response signal and the attributes of the description characteristics of the important signal nodes of the sample medical response signal to obtain a first association set, wherein the first association set comprises a plurality of important signal nodes, each important signal node comprises the important signal node of the target medical response signal after screening according to the attributes of the description characteristics and the important signal node in the sample medical response signal associated with the important signal node of the target medical response signal after screening;
screening important signal nodes in the first association set according to signal errors and signal correction among the important signal nodes of the important signal nodes in the first association set to obtain a second association set;
and screening the second association set according to the attribute of the description characteristics of the important signal nodes in the second association set to obtain the target association set.
8. The system of claim 7, wherein the data processing terminal is specifically configured to:
determining a second important signal node ranked first and a third important signal node ranked second according to the description feature relevance of the first important signal node in the target medical response signal, wherein the second important signal node and the third important signal node are important signal nodes in the sample medical response signal;
determining whether to screen the first important signal node according to the description features of the first important signal node and the attributes of the description features of the second important signal node, and the attributes of the description features of the second important signal node and the attributes of the description features of the third important signal node;
and if the first important signal node is determined not to be screened, using the important signal node formed by the first important signal node and the second important signal node as one important signal node in the first association set.
9. The system of claim 7, wherein the data processing terminal is specifically configured to:
counting signal errors and signal corrections among important signal nodes of all the important signal nodes in the first association set to obtain a first matrix;
taking the important signal node in the error vector with the largest value in the first matrix as the important signal node in the second correlation set;
wherein the data processing terminal is specifically configured to:
if two important signal nodes in the second association set both include a fourth important signal node, and the fourth important signal node is an important signal node in the sample medical response signal, the important signal node with the small description feature attribute of the two important signal nodes where the fourth important signal node is located is taken as the important signal node in the target association set, wherein the description feature attribute of the important signal node is the feature attribute of the two important signal nodes in the important signal nodes.
10. The system according to any one of claims 6 to 9, wherein the data processing terminal is specifically configured to:
and obtaining the signal content identification result according to the description characteristic attribute of each important signal node in the target association set.
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