CN111324671A - Biomedical high-speed information processing and analyzing system based on big data technology - Google Patents
Biomedical high-speed information processing and analyzing system based on big data technology Download PDFInfo
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Abstract
The invention discloses a biomedical high-speed information processing and analyzing system based on big data technology, which comprises a hospital government platform, a data integration module and a big data technology module, wherein the data integration module comprises hospital system information, gene database information, sensor acquisition information and equipment acquisition information based on the hospital government platform; the invention realizes the distributed storage of a relational database and a NoSQL database, can construct a multi-layer data model of a data warehouse, realizes the free search of historical case data by utilizing the powerful function of an Elasticissearch search engine, can separately store private data and common data by the multi-layer data model, can perform multiple backups of the data, prevents the loss of important data, and has perfect function support capability of the data warehouse and the database.
Description
Technical Field
The invention relates to the technical field of biomedical systems, in particular to a biomedical high-speed information processing and analyzing system based on a big data technology.
Background
Along with the progress of the times and the development of scientific technology, the research of the biological medicine becomes more and more important, the analysis and the processing of some data information are particularly important in the field of the biological medicine research, and the mature products which can be practically applied at home and abroad are recently reported and are mainly in the research level;
in some biomedical manufacturers, aiming at researched data information, the main means is to modify and use HIS as an information integration platform, thus aggravating HIS duplicate load, lacking key components and functions of information integration and sharing, lacking perfect functional support of a data warehouse and a database, lacking strong support of a data analysis and mining algorithm and having insufficient safety, therefore, the invention provides a biomedical high-speed information processing and analyzing system based on a big data technology to solve the problems in the prior art.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a biomedical high-speed information processing and analyzing system based on big data technology, which realizes distributed storage of a relational database and a NoSQL database, can construct a multi-layer data model of a data warehouse, and has perfect functional support capability of the data warehouse and the database.
In order to realize the purpose of the invention, the invention is realized by the following technical scheme: the biomedical high-speed information processing and analyzing system based on the big data technology comprises a hospital government platform, a data integration module and a big data technology module, wherein the data integration module comprises hospital system information, gene database information, sensor acquisition information and equipment acquisition information based on the hospital government platform and an Interne t network, the big data technology module comprises a Hadoop HDF S distributed architecture, an Elastic search server, a Kibana visualization platform, a mechanical learning machine learning and a genome calculation GenomeCalculation, and the big data technology module realizes the functions of data storage, data mining and data visualization;
the data integration module comprises medical term library construction, and perfect term service is established by adopting ICD-10 international disease standard so as to eliminate term difference among all business systems of the hospital and realize unified management of medical terms;
the Hadoop HDFS distributed architecture is developed by adopting AngularJS + NoSQL frames, a front-end interface is established by utilizing the AngularJS frames, server-end feedback is quickly established by utilizing NodeJS, front-end information is fed back, MongoDB is selected as a NoSQL database which is used as a non-relational database to reflect the relation among data and is used for data interaction;
in the big data module, an ELK (elastic search + Logstash + Kiban a) framework is adopted to deploy a search engine, an elastic search server is utilized to complete a distributed multi-user full-text search engine, a help platform carries out data management, and an L ogstash log analysis engine and a Kiban visualization platform are used to customize service requirements and assist the development of service flows.
The further improvement lies in that: in the data integration module, data integration conforms to international standards of HL7, IH E and XDS, a standard data conversion layer is established, a data structure is converted from an irregular rule into a regular rule, basic services are provided for data processing and data exchange of an upper layer, an integration engine supports the IHE standard and comprises an IHE exchange tool, an integration test function is built in the integration engine, and the configuration of each node in the process is contrasted and tested for grammatical and logic errors of codes.
The further improvement lies in that: the data integration module comprises ICD-10 and HL7 standards, data access conforms to Web service technical specifications, a data import interface facing to an HIS/PAC medical information system is provided, the data integration module is quickly adapted to the current heterogeneous distributed data environment, and data extraction and cleaning rules are defined.
The further improvement lies in that: the big data technology module adopts an extensible, high-performance and high-quality design framework and a software environment, provides an extensible high-performance solution for big data storage, processing, analysis, sharing and visualization in a safe and efficient mode, realizes distributed file storage, a distributed computing framework and a NoSQL database, realizes safe storage and high-performance computing of the big data, and has capacity dynamic expansion and disaster tolerance capabilities.
The further improvement lies in that: in the hospital government platform, a back end creates a new work flow through a script language, introduces work flow management, dynamically analyzes information flowing through a system, is used for tracking process information, managing the flow and following data changes, and meanwhile, a log backup of the back end records a work mode and an operation record, so that loss of business logic customized by a process is prevented.
The further improvement lies in that: the ElasticSearch search server performs cluster management, performs unified monitoring and management on HIE servers distributed locally or remotely, utilizes an ELK technology to realize query and search on a local or remote HIE system, performs distributed cluster management and control based on a distributed storage mode of a Hadoop technology, and ensures data security by utilizing a mode of storing redundant data.
The invention has the beneficial effects that: the invention realizes the distributed storage of a relational database and a NoSQL database, can construct a data warehouse multilayer data model, realizes the free search of historical case data by utilizing the powerful function of an Elastic search engine, can separately store private data and common data by the hierarchical data model, can perform multiple backups of the data, prevents the loss of important data, has perfect function supporting capability of the data warehouse and the database, realizes a distributed computing framework by a big data technology module, realizes the safe storage and high-performance computation of big data, supports a parallelization statistical algorithm and a machine learning basic algorithm library, can process a big data set, supports the research and development of the application function of precise medical big data, has strong data analysis and mining algorithm supporting capability, simultaneously supports a key deployment function of the cluster, supports a graphical interface to realize the resource monitoring of the big data cluster, the method adopts cluster management to uniformly monitor and manage HIE servers distributed locally or remotely, carries out real-time error tracking on the system, supports various security and encryption technologies, can encrypt data according to different requirements of service data, prevents the data from being stolen, can achieve the finest security management on user access control, in addition, provides flexible import interface expansion, helps flexible exchange with external application, improves the system efficiency, combines big data with cloud, enables the platform to support multiple tenants, can establish computing clusters as required, destroys as required, and is more convenient to use.
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FIG. 1 is a system architecture diagram of the present invention.
Detailed Description
In order to further understand the present invention, the following detailed description will be made with reference to the following examples, which are only used for explaining the present invention and are not to be construed as limiting the scope of the present invention.
According to fig. 1, the present embodiment provides a biomedical high-speed information processing and analyzing system based on big data technology, which includes a hospital government platform, a data integration module and a big data technology module, wherein the data integration module includes hospital system information, gene database information, sensor acquisition information and device acquisition information based on the hospital government platform and the Internet, the big data technology module includes a hadoop hdfs distributed architecture, an Elastic Search server, a Kibana visualization platform, a mechanical learning machine learning and a genome computing GenomeCalculation, and the big data technology module implements functions including data storage, data mining and data visualization;
the data integration module comprises medical term library construction, and perfect term service is established by adopting ICD-10 international disease standard so as to eliminate term difference among all business systems of the hospital and realize unified management of medical terms;
the Hadoop HDFS distributed architecture is developed by adopting AngularJS + NoSQL frames, a front-end interface is established by utilizing the AngularJS frames, server-end feedback is quickly established by utilizing NodeJS, front-end information is fed back, MongoDB is selected as a NoSQL database which is used as a non-relational database to reflect the relation among data and is used for data interaction;
in the big data module, an ELK (elastic search + Logstash + Kiban a) framework is adopted to deploy a search engine, an elastic search server is utilized to complete a distributed multi-user full-text search engine, a help platform carries out data management, and an L ogstash log analysis engine and a Kiban visualization platform are used to customize service requirements and assist the development of service flows.
In the data integration module, data integration conforms to international standards of HL7, IHE and XDS, a standard data conversion layer is established, a data structure is converted from irregular to regular, basic service is provided for data processing and data exchange of an upper layer, an integration engine supports the IHE standard and comprises an IH E exchange tool, an integration test function is built in the integration engine, and the configuration of each node in the process is contrasted and tested for grammatical and logic errors of codes.
The data integration module comprises ICD-10 and HL7 standards, data access conforms to Web service technical specifications, a data import interface facing to an HIS/PAC medical information system is provided, the data integration module is quickly adapted to the current heterogeneous distributed data environment, and data extraction and cleaning rules are defined.
The big data technology module adopts an extensible, high-performance and high-quality design framework and a software environment, provides an extensible high-performance solution for big data storage, processing, analysis, sharing and visualization in a safe and efficient mode, realizes distributed file storage, a distributed computing framework and a NoSQL database, realizes safe storage and high-performance computing of the big data, and has capacity dynamic expansion and disaster tolerance capabilities.
In the hospital government platform, a back end creates a new work flow through a script language, introduces work flow management, dynamically analyzes information flowing through a system, is used for tracking process information, managing the flow and following data changes, and meanwhile, a log backup of the back end records a work mode and an operation record, so that loss of business logic customized by a process is prevented.
The ElasticSearch search server performs cluster management, performs unified monitoring and management on HIE servers distributed locally or remotely, utilizes an ELK technology to realize query and search on a local or remote HIE system, performs distributed cluster management and control based on a distributed storage mode of a Hadoop technology, and ensures data security by utilizing a mode of storing redundant data.
The invention realizes the distributed storage of a relational database and a NoSQL database, can construct a multilayer data model of a data warehouse, realizes the free search of historical case data by utilizing the powerful function of an Elasticissearch search engine, can separately store private data and common data by utilizing the hierarchical data model, can perform multiple backups of the data, prevents the loss of important data, has perfect function supporting capability of the data warehouse and the database, realizes a distributed computing framework by a big data technology module, realizes the safe storage and high-performance computation of big data, supports a parallelization statistical algorithm and a machine learning basic algorithm library, can process big data sets, supports the research and development of the application function of precise medical big data, has strong data analysis and mining algorithm supporting capability, simultaneously supports a key deployment function of the sets, supports a graphical interface to realize the resource monitoring of the big data sets, the method adopts cluster management to uniformly monitor and manage HIE servers distributed locally or remotely, carries out real-time error tracking on the system, supports various security and encryption technologies, can encrypt data according to different requirements of service data, prevents the data from being stolen, can achieve the finest security management on user access control, in addition, provides flexible import interface expansion, helps flexible exchange with external application, improves the system efficiency, combines big data with cloud, enables the platform to support multiple tenants, can establish computing clusters as required, destroys as required, and is more convenient to use.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. The biomedical high-speed information processing and analyzing system based on big data technology is characterized in that: the system comprises a hospital government platform, a data integration module and a big data technology module, wherein the data integration module comprises hospital system information, gene database information, sensor acquisition information and equipment acquisition information based on the hospital government platform and the Internet, the big data technology module comprises a Hadoop HDFS distributed architecture, an elastic search server, a Kibana visualization platform, a mechanical learning machine learning and genome calculation, and the big data technology module realizes the functions of data storage, data mining and data visualization;
the data integration module comprises medical term library construction, and perfect term service is established by adopting ICD-10 international disease standard so as to eliminate term difference among all business systems of the hospital and realize unified management of medical terms;
the Hadoop HDFS distributed architecture is developed by adopting AngularJS + NoSQL frames, a front-end interface is established by utilizing the AngularJS frames, server-end feedback is quickly established by utilizing NodeJS, front-end information is fed back, MongoDB is selected as a NoSQL database which is used as a non-relational database to reflect the relation among data and is used for data interaction;
in the big data module, an ELK (elastic search + Logstash + Kibana) framework is adopted to deploy a search engine, an elastic search server is utilized to complete a distributed multi-user full-text search engine, a help platform is used for data management, and a Logstash log analysis engine and a Kibana visualization platform are used for customizing service requirements and assisting the development of service flows.
2. The biomedical high-speed information processing and analyzing system based on big data technology according to claim 1, characterized in that: in the data integration module, data integration conforms to international standards of HL7, IHE and XDS, a standard data conversion layer is established, a data structure is converted from irregular to regular, basic service is provided for data processing and data exchange of an upper layer, an integration engine supports the IHE standard, an IHE exchange tool is included, an integration test function is built in the integration engine, and the configuration of each node in the process is contrasted and tested for grammatical and logic errors of codes.
3. The biomedical high-speed information processing and analyzing system based on big data technology according to claim 1, characterized in that: the data integration module comprises ICD-10 and HL7 standards, data access conforms to Web service technical specifications, a data import interface facing to a HIS/PACS medical information system is provided, the data integration module is quickly adapted to the current heterogeneous distributed data environment, and data extraction and cleaning rules are defined.
4. The biomedical high-speed information processing and analyzing system based on big data technology according to claim 1, characterized in that: the big data technology module adopts an extensible, high-performance and high-quality design framework and a software environment, provides an extensible high-performance solution for big data storage, processing, analysis, sharing and visualization in a safe and efficient mode, realizes distributed file storage, a distributed computing framework and a NoSQL database, realizes safe storage and high-performance computing of the big data, and has capacity dynamic expansion and disaster tolerance capabilities.
5. The biomedical high-speed information processing and analyzing system based on big data technology according to claim 1, characterized in that: in the hospital government platform, a back end creates a new work flow through a script language, introduces work flow management, dynamically analyzes information flowing through a system, is used for tracking process information, managing the flow and following data changes, and meanwhile, a log backup of the back end records a work mode and an operation record, so that loss of business logic customized by a process is prevented.
6. The biomedical high-speed information processing and analyzing system based on big data technology according to claim 1, characterized in that: the ElasticSearch search server performs cluster management, performs unified monitoring and management on HIE servers distributed locally or remotely, utilizes an ELK technology to realize query and search on a local or remote HIE system, performs distributed cluster management and control based on a distributed storage mode of a Hadoop technology, and ensures data security by utilizing a mode of storing redundant data.
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| CN112349404A (en) * | 2020-11-03 | 2021-02-09 | 中国人民解放军总医院 | Multi-center medical equipment big data cloud platform based on cloud-edge-end architecture |
| CN113223621A (en) * | 2021-05-17 | 2021-08-06 | 上海交通大学 | Full-chain data analysis system for biomedicine |
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