CN115033693A - Knowledge management method of medical cognitive intelligent scientific research platform - Google Patents
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- 238000013499 data model Methods 0.000 claims abstract description 19
- 238000012216 screening Methods 0.000 claims abstract description 6
- 238000000034 method Methods 0.000 claims description 16
- 230000005540 biological transmission Effects 0.000 claims description 7
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- 230000000694 effects Effects 0.000 claims description 4
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- G16H70/00—ICT specially adapted for the handling or processing of medical references
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Abstract
The invention discloses a knowledge management method of a medical cognitive intelligent scientific research platform, which relates to the technical field of medical cognitive intelligent scientific research platforms and comprises the following steps: s1, acquiring knowledge data; s2, data classification recording; s3, dynamically evaluating data; s4, constructing a knowledge data model; s5, managing identity authentication; and S6, searching and retrieving data. The knowledge management method of the medical cognitive intelligent scientific research platform ensures authenticity and validity of acquired data through data screening when the knowledge data in each field is acquired, guarantees are provided for management of knowledge data of a follow-up platform, generation of a safety protocol is carried out on the data which are dynamically evaluated, safety of the data entering a system platform is ensured, the condition that the data leak is avoided, classified storage of the acquired data in the corresponding fields is carried out, the condition that confusion occurs among the data due to unified storage of the data, invalid effective data is caused is effectively avoided, and meanwhile validity of establishment of a knowledge data model is ensured.
Description
Technical Field
The invention relates to the technical field of medical cognitive intelligent scientific research platforms, in particular to a knowledge management method of a medical cognitive intelligent scientific research platform.
Background
By means of intelligent equipment of an internet of things/cloud computing technology, an artificial intelligence expert system and an embedded system, a complete internet of things medical system can be built, intelligent medical treatment is achieved by creating a health archive regional medical information platform and utilizing the most advanced internet of things technology to achieve interaction between a patient and medical staff, a medical institution and medical equipment, informatization is achieved gradually, the medical industry is integrated with high technologies such as more artificial intelligence and sensing technology in the near future, medical service is enabled to be truly intelligent, and medical cognitive intelligent scientific research platforms are used more and more generally.
The conventional medical cognitive intelligent scientific research platform cannot effectively guarantee the effectiveness of knowledge data acquisition, management and retrieval of knowledge data are not convenient for managers, and the safety of the system platform is low.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a knowledge management method of a medical cognitive intelligent scientific research platform, which solves the problems in the background technology.
In order to achieve the purpose, the invention is realized by the following technical scheme, and the knowledge management method of the medical cognitive intelligent scientific research platform comprises the following steps:
s1, acquiring knowledge data
Firstly, classifying, acquiring and collecting medical cognitive knowledge data in different fields, screening effective knowledge data on the acquired knowledge data, and eliminating ineffective knowledge data to ensure the effectiveness and authenticity of the acquired knowledge data;
s2, data classification record
Classifying the effective knowledge data acquired from the knowledge data acquired in the S1 according to the corresponding fields, then carrying out corresponding channel transmission on the knowledge data in different fields to avoid confusion of the knowledge data in the transmission process, and then recording and storing the corresponding field data in the corresponding knowledge database;
s3, dynamic evaluation of data
Performing data dynamic evaluation on the data which is stored in the S2 data classification record, enhancing the relevance among the data, improving the activity of knowledge data, avoiding knowledge redundancy and knowledge conflict, improving the discovery power of knowledge, and then performing safety protocol generation on the knowledge data which is subjected to the dynamic evaluation;
s4, constructing a knowledge data model
Acquiring knowledge atoms from a corresponding knowledge database according to set keywords, establishing a knowledge atom data set based on the keywords, establishing a knowledge data model through the knowledge atom data set through a learning algorithm, constructing a keyword data set, calculating the similarity between entity data in the knowledge model and the keywords, acquiring matched entity data, and generating a data retrieval path according to the keywords;
s5 management identity verification
When the administrator searches and checks and operates corresponding knowledge data, identity authentication of the administrator is required, the administrator can enter the system platform to search and check the knowledge data when the identity authentication is qualified, and the system platform records the identity and the IP address of the administrator when the identity authentication is unqualified, so that related personnel can conveniently check the personnel, and the management safety of the whole intelligent scientific research platform system is ensured;
s6, searching data
After the identity authentication is managed and the system platform is accessed through S5, managers can search knowledge data in corresponding fields through keywords, search work of corresponding search channels is carried out on the knowledge data in the corresponding fields, detection of the knowledge data in multiple knowledge fields can be carried out simultaneously, therefore, the managers can conveniently compare the multiple data, and the system platform records the access of the managers.
Optionally, the invalid data removed in the knowledge data obtaining process in step S1 includes confusion data, messy code data, and duplicate data.
Optionally, in the step S4, the knowledge atoms in the process of constructing the knowledge data model include entity knowledge data and relationship knowledge data.
Optionally, in the step S4, the learning algorithm established by the knowledge data model in the knowledge data model establishing process is specifically a deep neural network algorithm.
Optionally, the step S5 manages the authentication process, where the authentication process includes digital ID, fingerprint and face data authentication.
Optionally, the access record in the S6 data search and retrieval process includes a search keyword, an access identity, an access time, and a logout time.
The invention provides a knowledge management method of a medical cognitive intelligent scientific research platform, which has the following beneficial effects: the knowledge management method of the medical cognitive intelligent scientific research platform ensures the authenticity and the validity of acquired data through data screening when acquiring knowledge data of each field, provides guarantee for the knowledge data management of a subsequent platform, generates a safety protocol for the data which is dynamically evaluated, ensures the safety of the data entering a system platform, avoids the condition of data leakage, effectively avoids the condition of data confusion and invalid effective data caused by unified data storage by classifying and storing the acquired data of the corresponding field, ensures the validity of knowledge data model establishment, improves the retrieval efficiency of the subsequent managers on the knowledge data, provides guarantee for the long-term establishment of the knowledge data through a deep neural network algorithm, and matches the record of the retrieved data through the identity verification of the managers, the safety of the whole intelligent scientific research platform system management is ensured.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to specific embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
A knowledge management method of a medical cognitive intelligent scientific research platform comprises the following specific steps:
s1, acquiring knowledge data
Firstly, classifying, acquiring and collecting medical cognitive knowledge data in different fields, screening effective knowledge data on the acquired knowledge data, and eliminating ineffective knowledge data to ensure the effectiveness and authenticity of the acquired knowledge data;
invalid data removed in the knowledge data acquisition process comprise confusion data, messy code data and repeated data;
s2, data classification record
Classifying the effective knowledge data acquired from the knowledge data acquired in the S1 according to the corresponding fields, then carrying out corresponding channel transmission on the knowledge data in different fields to avoid confusion of the knowledge data in the transmission process, and then recording and storing the corresponding field data in the corresponding knowledge database;
s3, dynamic evaluation of data
The data stored in the data classification records of S2 are dynamically evaluated, the relevance among the data is enhanced, the activity of knowledge data is improved, knowledge redundancy and knowledge conflict are avoided, the knowledge discovery power is improved, and then the safety protocol is generated on the knowledge data which is dynamically evaluated;
s4, constructing a knowledge data model
Acquiring knowledge atoms from a corresponding knowledge database according to the set keywords, establishing a knowledge atom data set based on the keywords, establishing a knowledge data model through the knowledge atom data set through a learning algorithm, constructing a keyword data set, calculating the similarity between entity data and the keywords in the knowledge model, acquiring matched entity data, and generating a data retrieval path according to the keywords;
in the process of constructing a knowledge data model, knowledge atoms comprise entity knowledge data and relation knowledge data;
establishing a learning algorithm, specifically a deep neural network algorithm, by using the knowledge data model in the knowledge data model establishing process;
s5 management identity verification
When the administrator searches and checks and operates corresponding knowledge data, identity authentication of the administrator is required, the administrator can enter the system platform to search and check the knowledge data when the identity authentication is qualified, and the system platform records the identity and the IP address of the administrator when the identity authentication is unqualified, so that related personnel can conveniently check the personnel, and the management safety of the whole intelligent scientific research platform system is ensured;
the identity authentication in the management identity authentication process comprises digital ID, fingerprint and face data authentication;
s6, searching data
After identity authentication is managed and enters a system platform through S5, a manager can search knowledge data of the corresponding field through a keyword, search the knowledge data of the corresponding field through a corresponding search channel, and detect the knowledge data of multiple knowledge fields at the same time, so that the manager can conveniently compare the multiple data, and the system platform records the access of the manager;
the access record in the data searching and retrieving process comprises a retrieval keyword, an access identity, access time and logout time.
To sum up, the knowledge management method of the medical cognitive intelligent scientific research platform comprises the following specific steps:
firstly, classifying, acquiring and collecting medical cognitive knowledge data in different fields, screening effective knowledge data from the acquired knowledge data, and eliminating ineffective knowledge data to ensure the effectiveness and authenticity of the acquired knowledge data;
then classifying the effective knowledge data acquired from the knowledge data acquired in the S1 according to the knowledge data in the corresponding field, then transmitting the knowledge data in different fields through corresponding channels, avoiding confusion of the knowledge data in the transmission process, and then recording and storing the corresponding field data in a corresponding knowledge database;
then, carrying out data dynamic evaluation on the data which are stored in the S2 data classification record, enhancing the relevance among the data, improving the activity of knowledge data, avoiding knowledge redundancy and knowledge conflict, improving the discovery power of knowledge, and then carrying out safety protocol generation on the knowledge data which are subjected to dynamic evaluation;
acquiring knowledge atoms from a corresponding knowledge database according to set keywords, establishing a knowledge atom data set based on the keywords, establishing a knowledge data model through the knowledge atom data set through a learning algorithm, constructing a keyword data set, calculating the similarity between entity data in the knowledge model and the keywords, acquiring matched entity data, and generating a data retrieval path according to the keywords;
when the administrator searches and checks and operates corresponding knowledge data, identity authentication of the administrator is required, the administrator can enter the system platform to search and check the knowledge data when the identity authentication is qualified, and the system platform records the identity and the IP address of the administrator when the identity authentication is unqualified, so that related personnel can conveniently check the personnel, and the management safety of the whole intelligent scientific research platform system is ensured;
and finally, after the identity authentication is managed and enters the system platform through S5, managers can search knowledge data in corresponding fields through keywords, search work of corresponding search channels is carried out on the knowledge data in the corresponding fields, detection of the knowledge data in multiple knowledge fields can be carried out simultaneously, so that the managers can conveniently compare the multiple data, and the system platform records the access of the managers.
Claims (6)
1. A knowledge management method of a medical cognitive intelligent scientific research platform is characterized by comprising the following steps:
s1, acquiring knowledge data
Firstly, classifying, acquiring and collecting medical cognitive knowledge data in different fields, screening effective knowledge data from the acquired knowledge data, and eliminating ineffective knowledge data to ensure the effectiveness and authenticity of the acquired knowledge data;
s2, data classification record
Classifying the effective knowledge data acquired from the knowledge data acquired in the S1 according to the corresponding fields, then carrying out corresponding channel transmission on the knowledge data in different fields to avoid confusion of the knowledge data in the transmission process, and then recording and storing the corresponding field data in the corresponding knowledge database;
s3, dynamic evaluation of data
The data stored in the data classification records of S2 are dynamically evaluated, the relevance among the data is enhanced, the activity of knowledge data is improved, knowledge redundancy and knowledge conflict are avoided, the knowledge discovery power is improved, and then the safety protocol is generated on the knowledge data which is dynamically evaluated;
s4, constructing a knowledge data model
Acquiring knowledge atoms from a corresponding knowledge database according to set keywords, establishing a knowledge atom data set based on the keywords, establishing a knowledge data model through the knowledge atom data set through a learning algorithm, constructing a keyword data set, calculating the similarity between entity data in the knowledge model and the keywords, acquiring matched entity data, and generating a data retrieval path according to the keywords;
s5 management identity verification
When the administrator searches and checks and operates corresponding knowledge data, identity authentication of the administrator is required, the administrator can enter the system platform to search and check the knowledge data when the identity authentication is qualified, and the system platform records the identity and the IP address of the administrator when the identity authentication is unqualified, so that related personnel can conveniently check the personnel, and the management safety of the whole intelligent scientific research platform system is ensured;
s6, searching data
After the identity authentication is managed and the system platform is accessed through S5, managers can search knowledge data in corresponding fields through keywords, search work of corresponding search channels is carried out on the knowledge data in the corresponding fields, detection of the knowledge data in multiple knowledge fields can be carried out simultaneously, therefore, the managers can conveniently compare the multiple data, and the system platform records the access of the managers.
2. The knowledge management method of the medical cognitive intelligent scientific research platform according to claim 1, which comprises the following steps: the invalid data removed in the knowledge data acquisition process in the step S1 includes confusion data, messy code data, and duplicate data.
3. The knowledge management method of the medical cognitive intelligent scientific research platform according to claim 1, which comprises the following steps: in the step S4, the knowledge atoms include entity knowledge data and relationship knowledge data in the process of constructing the knowledge data model.
4. The knowledge management method of the medical cognitive intelligent scientific research platform according to claim 1, which comprises the following steps: in the step S4, the learning algorithm specifically is established by the knowledge data model in the process of establishing the knowledge data model.
5. The knowledge management method of the medical cognitive intelligent scientific research platform according to claim 1, which comprises the following steps: the step S5 manages the authentication process including digital ID, fingerprint and face data authentication.
6. The knowledge management method for the medical cognitive intelligent scientific research platform according to claim 1, which is characterized by comprising the following steps: the access record in the S6 data search and retrieval process includes a search keyword, an access identity, an access time, and a logout time.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109241278A (en) * | 2018-07-18 | 2019-01-18 | 绍兴诺雷智信息科技有限公司 | Scientific research knowledge management method and system |
| EP3458986A1 (en) * | 2016-05-16 | 2019-03-27 | Koninklijke Philips N.V. | Clinical report retrieval and/or comparison |
| US20210398658A1 (en) * | 2018-10-10 | 2021-12-23 | Healthpointe Solutions, Inc. | Cognitive artificial-intelligence based population management |
| CN114546985A (en) * | 2022-01-20 | 2022-05-27 | 深圳市企慧通信息技术有限公司 | Enterprise intelligent knowledge management system with learning ability |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3458986A1 (en) * | 2016-05-16 | 2019-03-27 | Koninklijke Philips N.V. | Clinical report retrieval and/or comparison |
| CN109241278A (en) * | 2018-07-18 | 2019-01-18 | 绍兴诺雷智信息科技有限公司 | Scientific research knowledge management method and system |
| US20210398658A1 (en) * | 2018-10-10 | 2021-12-23 | Healthpointe Solutions, Inc. | Cognitive artificial-intelligence based population management |
| CN114546985A (en) * | 2022-01-20 | 2022-05-27 | 深圳市企慧通信息技术有限公司 | Enterprise intelligent knowledge management system with learning ability |
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