CN113903473A - Medical information intelligent interaction method and system based on artificial intelligence - Google Patents
Medical information intelligent interaction method and system based on artificial intelligence Download PDFInfo
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Abstract
According to the method and the system for medical information intelligent interaction based on artificial intelligence, medical interaction information is obtained, an original medical session subject set in the medical interaction information is mined, the original medical session subject set is loaded to a preset mining and screening network, so that a first identification condition in the original medical session subject set is obtained, and an identification condition of non-example medical attribute content serves as a second identification condition; the medical attribute content identification condition is verified, the medical attribute content of which the identification condition accords with the preset identification condition after verification is determined as the medical attribute content with the abnormal mark, the mining screening results of a plurality of groups of medical session topics are verified, and the pointing content of the abnormal mark is determined according to the verification processing result, so that the accuracy and the reliability of the abnormal mark screening result can be improved; the original abnormal mark screening result can be generated more accurately based on the medical attribute content of all the abnormal marks.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a medical information intelligent interaction method and system based on artificial intelligence.
Background
As artificial intelligence is specifically applied to hospitals, there may be a problem of confusion of medical information interaction, so that it is difficult to perform precise interaction, and therefore, a method for intelligent interaction of medical information is urgently needed to solve the above technical problem.
Disclosure of Invention
In view of this, the present application provides a method and system for medical information intelligent interaction based on artificial intelligence.
In a first aspect, a method for medical information intelligent interaction based on artificial intelligence is provided, the method comprising:
acquiring medical interaction information, and mining an original medical session theme set in the medical interaction information, wherein the original medical session theme set comprises a medical session theme with preset calculation indexes;
loading the original medical session subject set to a preset mining and screening network so as to take the identification condition of example medical attribute contents of the medical session subjects in the original medical session subject set as a first identification condition and take the identification condition of non-example medical attribute contents as a second identification condition;
and verifying the medical attribute content identification condition of the medical session theme in the original medical session theme set, determining the medical attribute content of which the identification condition is in accordance with the preset identification condition after verification as the medical attribute content with the abnormal mark, and generating an original abnormal mark screening result based on all the medical attribute contents with the abnormal marks.
In a separately implemented embodiment, the method further comprises:
obtaining an optimized medical session theme after an original medical session theme set in the medical interaction information;
loading the optimized medical session theme to the preset mining screening network to obtain an optimized abnormal marking screening result of the optimized medical session theme;
and optimizing according to the content of the existing relationship between the original abnormal mark screening result and the optimized abnormal mark screening result to obtain the pointed content of the abnormal mark.
In an embodiment of independent implementation, the optimizing the content according to the existing relationship between the original abnormal mark screening result and the optimized abnormal mark screening result to obtain the pointed content of the abnormal mark includes:
determining the correlation condition of the original abnormal mark screening result and the optimized abnormal mark screening result;
and on the premise that the association condition accords with a preset association condition, optimizing the original abnormal mark screening result according to the optimized abnormal mark screening result so as to optimize the pointing content of the abnormal mark.
In a separately implemented embodiment, the method further comprises:
acquiring a mining medical session theme in the medical interaction information, mining abnormal mark pointing contents corresponding to an original abnormal mark screening result in the mining medical session theme, and taking the identification condition of the remaining non-abnormal mark pointing contents as a third identification condition;
determining a minimum screening unit of the mining medical session theme based on the identification conditions of abnormal mark pointing content and non-abnormal mark pointing content of the mining medical session theme after mining processing;
determining a mining result of each identification condition in the mining medical session subject after mining processing, and taking the mining result larger than or smaller than 0 as a fourth identification condition, wherein the fourth identification condition is in accordance with the third identification condition;
determining a maximum screening unit of the mining medical session topic based on the mining result of the updated mining medical session topic; and obtaining the abnormal marking condition of the mining medical conversation theme according to the minimum screening unit and the maximum screening unit of the mining medical conversation theme.
In an independently implemented embodiment, the obtaining the abnormal marking condition of the mining medical session topic according to the minimum filtering unit and the maximum filtering unit of the mining medical session topic includes:
determining a screening unit of the mining medical session theme according to the identification condition of the mining medical session theme; and obtaining the abnormal marking condition of the mining medical conversation theme according to the screening unit, the minimum screening unit and the maximum screening unit of the mining medical conversation theme.
In an independently implemented embodiment, the screening unit for determining the mining medical session topic according to the identification condition of the mining medical session topic includes:
obtaining the identification condition of each medical attribute content on the mining medical session theme;
determining mining results of each medical attribute content and the adaptive medical attribute content in sequence;
and checking and processing the mining results of all medical attribute contents in the mining medical session theme to obtain the screening unit of the mining medical session theme.
In a second aspect, a system for intelligent interaction of medical information based on artificial intelligence is provided, which comprises a processor and a memory, which are communicated with each other, wherein the processor is used for reading a computer program from the memory and executing the computer program to realize the method.
According to the method and the system for medical information intelligent interaction based on artificial intelligence, medical interaction information is obtained, an original medical session subject set in the medical interaction information is mined, and the original medical session subject set is loaded to a preset mining and screening network, so that the identification condition of example medical attribute content of a medical session subject in the original medical session subject set is used as a first identification condition, and the identification condition of non-example medical attribute content is used as a second identification condition; the medical attribute content identification condition of the medical session theme in the original medical session theme set is verified, the medical attribute content of which the identification condition is in accordance with the preset identification condition after verification is determined as the medical attribute content with the abnormal mark, the mining screening result of a plurality of groups of medical session themes is verified, and the pointing content of the abnormal mark is determined according to the verification processing result, so that the accuracy and the reliability of the screening result of the abnormal mark can be improved; the original abnormal mark screening result can be generated more accurately based on the medical attribute content of all the abnormal marks.
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 method for interacting medical information based on artificial intelligence according to an embodiment of the present application.
Fig. 2 is a block diagram of an apparatus for interacting medical information based on artificial intelligence according to an embodiment of the present application.
Fig. 3 is an architecture diagram of a system for interacting medical information based on artificial intelligence 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 method for medical information intelligent interaction based on artificial intelligence is shown, which may include the following steps 100-300.
It can be understood that, when the contents described in the above steps 100 to 300 are executed, by obtaining the medical interaction information, mining an original medical session topic set in the medical interaction information, and loading the original medical session topic set to the preset mining screening network, the identification condition of the example medical attribute content of the medical session topic in the original medical session topic set is taken as a first identification condition, and the identification condition of the non-example medical attribute content is taken as a second identification condition; the medical attribute content identification condition of the medical session theme in the original medical session theme set is verified, the medical attribute content of which the identification condition is in accordance with the preset identification condition after verification is determined as the medical attribute content with the abnormal mark, the mining screening result of a plurality of groups of medical session themes is verified, and the pointing content of the abnormal mark is determined according to the verification processing result, so that the accuracy and the reliability of the screening result of the abnormal mark can be improved; the original abnormal mark screening result can be generated more accurately based on the medical attribute content of all the abnormal marks.
Based on the above basis, the following descriptions of step a 1-step a3 can also be included.
Step a1, obtaining the optimized medical session subject after the original medical session subject set in the medical interactive information.
Step a2, loading the optimized medical session topic to the preset mining screening network to obtain an optimized abnormal mark screening result of the optimized medical session topic.
Step a3, optimizing according to the content of the relationship between the original abnormal mark screening result and the optimized abnormal mark screening result to obtain the pointed content of the abnormal mark.
It can be understood that, when the content described in the above steps a 1-a 3 is executed, the accuracy of pointing to the content of the abnormal mark is further improved by continuously optimizing the medical session topic.
In this embodiment, when optimizing the content according to the relationship between the original abnormal flag screening result and the optimized abnormal flag screening result, there is a problem that the content of the relationship is inaccurate, so that it is difficult to accurately obtain the pointed content of the abnormal flag, and in order to improve the above technical problem, the step of optimizing the content according to the relationship between the original abnormal flag screening result and the optimized abnormal flag screening result, which is described in step a3, to obtain the pointed content of the abnormal flag may specifically include the following content described in step a31 and step a 32.
Step a31, determining the correlation between the original abnormal mark screening result and the optimized abnormal mark screening result.
Step a32, on the premise that the association condition is in accordance with a preset association condition, optimizing the original abnormal mark screening result according to the optimized abnormal mark screening result to optimize the pointing content of the abnormal mark.
It can be understood that, when performing the content described in the above step a31 and step a32, and performing optimization according to the content having relationship between the original abnormal mark screening result and the optimized abnormal mark screening result, the problem of inaccurate content having relationship is improved, so that the pointed content of the abnormal mark can be accurately obtained.
Based on the above basis, the following descriptions of step s 1-step s4 can also be included.
Step s1, obtaining a mining medical session topic in the medical interaction information, mining the abnormal mark pointing content corresponding to the original abnormal mark screening result in the mining medical session topic, and taking the recognition condition of the remaining non-abnormal mark pointing content as a third recognition condition.
And step s2, determining the minimum screening unit of the mining medical session topic based on the identification conditions of the abnormal mark pointing content and the non-abnormal mark pointing content of the mining medical session topic after mining processing.
And step s3, determining the mining result of each identification condition in the mining medical session subject after the mining processing, and taking the mining result greater than or less than 0 as a fourth identification condition, wherein the fourth identification condition is in accordance with the third identification condition.
Step s4, determining the maximum screening unit of the mining medical session topic based on the mining result of the updated mining medical session topic; and obtaining the abnormal marking condition of the mining medical conversation theme according to the minimum screening unit and the maximum screening unit of the mining medical conversation theme.
It is understood that the accuracy of the abnormal marking situation is improved by accurately performing the mining process while performing the contents described in the above-described steps s1 to s 4.
In this embodiment, when the minimum filtering unit and the maximum filtering unit of the mined medical session topic are used, there is a problem that the filtering is not accurate, so that it is difficult to accurately obtain the abnormal marking condition of the mined medical session topic, in order to improve the above technical problem, the step of obtaining the abnormal marking condition of the mined medical session topic according to the minimum filtering unit and the maximum filtering unit of the mined medical session topic described in step s4 may specifically include the content described in the following step s 41.
Step s41, determining a screening unit of the mining medical session topic according to the identification condition of the mining medical session topic; and obtaining the abnormal marking condition of the mining medical conversation theme according to the screening unit, the minimum screening unit and the maximum screening unit of the mining medical conversation theme.
It can be understood that when the content described in the above step s41 is executed, the problem of inaccurate screening is improved according to the minimum screening unit and the maximum screening unit of the mined medical session topic, so that the abnormal marking condition of the mined medical session topic can be accurately obtained.
In this embodiment, when the identification condition of the mined medical session topic is determined, there is a problem that the identification condition is inaccurate, so that it is difficult to accurately determine the filtering unit of the mined medical session topic, and in order to improve the above technical problem, the step of determining the filtering unit of the mined medical session topic according to the identification condition of the mined medical session topic, which is described in step s41, may specifically include the contents described in step d1 to step d3 below.
And d1, obtaining the identification condition of each medical attribute content on the topic of the mining medical session.
And d2, determining the mining result of each medical attribute content and the adaptive medical attribute content in turn.
And d3, checking and processing the mining results of all medical attribute contents in the mining medical session topic to obtain a screening unit of the mining medical session topic.
It can be understood that, when the contents described in the above steps d 1-d 3 are executed, the problem of inaccurate identification situation is improved according to the identification situation of the mining medical session topic, so that the screening unit of the mining medical session topic can be accurately determined.
On the basis of the above, please refer to fig. 2, there is provided an apparatus 200 for interacting medical information based on artificial intelligence, which is applied to a system for interacting medical information based on artificial intelligence, the apparatus includes:
the topic mining module 210 is configured to obtain medical interaction information and mine an original medical session topic set in the medical interaction information, where the original medical session topic set includes a medical session topic with a preset calculation index;
a situation screening module 220, configured to load the original medical session topic set to a preset mining screening network, so as to use an identification situation of example medical attribute content of a medical session topic in the original medical session topic set as a first identification situation, and use an identification situation of non-example medical attribute content as a second identification situation;
and the result screening module 230 is configured to perform verification processing on the medical attribute content identification conditions of the medical session topics in the original medical session topic set, determine that the medical attribute content of which the identification condition meets the preset identification condition after the verification processing is the medical attribute content with the abnormal mark, and generate an original abnormal mark screening result based on all the medical attribute contents with the abnormal mark.
On the basis of the above, please refer to fig. 3, which shows a system 300 for interacting medical information based on artificial intelligence, comprising a processor 310 and a memory 320, which are communicated with each other, wherein the processor 310 is used for reading a 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, by obtaining the medical interaction information, mining the original medical session topic set in the medical interaction information, and loading the original medical session topic set to the preset mining and screening network, the identification condition of the example medical attribute content of the medical session topic in the original medical session topic set is used as the first identification condition, and the identification condition of the non-example medical attribute content is used as the second identification condition; the medical attribute content identification condition of the medical session theme in the original medical session theme set is verified, the medical attribute content of which the identification condition is in accordance with the preset identification condition after verification is determined as the medical attribute content with the abnormal mark, the mining screening result of a plurality of groups of medical session themes is verified, and the pointing content of the abnormal mark is determined according to the verification processing result, so that the accuracy and the reliability of the screening result of the abnormal mark can be improved; the original abnormal mark screening result can be generated more accurately based on the medical attribute content of all the abnormal marks.
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 by 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 (7)
1. A method for medical information intelligent interaction based on artificial intelligence, which is characterized by comprising the following steps:
acquiring medical interaction information, and mining an original medical session theme set in the medical interaction information, wherein the original medical session theme set comprises a medical session theme with preset calculation indexes;
loading the original medical session subject set to a preset mining and screening network so as to take the identification condition of example medical attribute contents of the medical session subjects in the original medical session subject set as a first identification condition and take the identification condition of non-example medical attribute contents as a second identification condition;
and verifying the medical attribute content identification condition of the medical session theme in the original medical session theme set, determining the medical attribute content of which the identification condition is in accordance with the preset identification condition after verification as the medical attribute content with the abnormal mark, and generating an original abnormal mark screening result based on all the medical attribute contents with the abnormal marks.
2. The method for artificial intelligence based medical information intelligence interaction of claim 1, wherein the method further comprises:
obtaining an optimized medical session theme after an original medical session theme set in the medical interaction information;
loading the optimized medical session theme to the preset mining screening network to obtain an optimized abnormal marking screening result of the optimized medical session theme;
and optimizing according to the content of the existing relationship between the original abnormal mark screening result and the optimized abnormal mark screening result to obtain the pointed content of the abnormal mark.
3. The method for interacting medical information based on artificial intelligence according to claim 2, wherein the optimizing the content according to the relationship between the original abnormal mark screening result and the optimized abnormal mark screening result to obtain the pointed content of the abnormal mark comprises:
determining the correlation condition of the original abnormal mark screening result and the optimized abnormal mark screening result;
and on the premise that the association condition accords with a preset association condition, optimizing the original abnormal mark screening result according to the optimized abnormal mark screening result so as to optimize the pointing content of the abnormal mark.
4. The method for artificial intelligence based medical information intelligence interaction of claim 1, wherein the method further comprises:
acquiring a mining medical session theme in the medical interaction information, mining abnormal mark pointing contents corresponding to an original abnormal mark screening result in the mining medical session theme, and taking the identification condition of the remaining non-abnormal mark pointing contents as a third identification condition;
determining a minimum screening unit of the mining medical session theme based on the identification conditions of abnormal mark pointing content and non-abnormal mark pointing content of the mining medical session theme after mining processing;
determining a mining result of each identification condition in the mining medical session subject after mining processing, and taking the mining result larger than or smaller than 0 as a fourth identification condition, wherein the fourth identification condition is in accordance with the third identification condition;
determining a maximum screening unit of the mining medical session topic based on the mining result of the updated mining medical session topic; and obtaining the abnormal marking condition of the mining medical conversation theme according to the minimum screening unit and the maximum screening unit of the mining medical conversation theme.
5. The method for interacting intelligent information about medical treatment based on artificial intelligence as claimed in claim 4, wherein the obtaining of abnormal marking condition of the topic of the mined medical treatment session according to the minimum filtering unit and the maximum filtering unit of the topic of the mined medical treatment session comprises:
determining a screening unit of the mining medical session theme according to the identification condition of the mining medical session theme; and obtaining the abnormal marking condition of the mining medical conversation theme according to the screening unit, the minimum screening unit and the maximum screening unit of the mining medical conversation theme.
6. The method for interacting intelligent information about medical treatment based on artificial intelligence as claimed in claim 5, wherein the step of determining the filtering unit of the topic of the mining medical treatment session according to the identification condition of the topic of the mining medical treatment session comprises:
obtaining the identification condition of each medical attribute content on the mining medical session theme;
determining mining results of each medical attribute content and the adaptive medical attribute content in sequence;
and checking and processing the mining results of all medical attribute contents in the mining medical session theme to obtain the screening unit of the mining medical session theme.
7. A system for intelligent interaction of medical information based on artificial intelligence, comprising a processor and a memory communicating with each other, the processor being adapted to read a computer program from the memory and execute it to perform the method of any one of claims 1 to 6.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114611478A (en) * | 2022-03-22 | 2022-06-10 | 孙向军 | Information processing method and system based on artificial intelligence and cloud platform |
| CN114691830A (en) * | 2022-03-31 | 2022-07-01 | 侯宇 | Network security analysis method and system based on big data |
| CN116719926A (en) * | 2023-08-10 | 2023-09-08 | 四川大学 | Congenital heart disease report data screening method and system based on intelligent medical treatment |
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2021
- 2021-10-26 CN CN202111246116.XA patent/CN113903473A/en not_active Withdrawn
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114611478A (en) * | 2022-03-22 | 2022-06-10 | 孙向军 | Information processing method and system based on artificial intelligence and cloud platform |
| CN114691830A (en) * | 2022-03-31 | 2022-07-01 | 侯宇 | Network security analysis method and system based on big data |
| CN116719926A (en) * | 2023-08-10 | 2023-09-08 | 四川大学 | Congenital heart disease report data screening method and system based on intelligent medical treatment |
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