Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Biomedicine missing data compensation method

A biomedical, missing data technology, applied in the biomedical field, can solve problems such as biomedical data gaps

Inactive Publication Date: 2013-06-26
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF3 Cites 34 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0011] The purpose of the invention is to solve the problem of vacant values ​​in biomedical data, and propose a method for making up for vacant data based on EM clustering-BP neural network

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Biomedicine missing data compensation method
  • Biomedicine missing data compensation method
  • Biomedicine missing data compensation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] In order to better illustrate the purpose and advantages of the present invention, the implementation of the method of the present invention will be further described in detail below in conjunction with the accompanying drawings and examples.

[0052] Using cluster sampling cross-sectional data of 59,839 people from scientific research institutes in Xicheng District and Haidian District of Beijing from February 2001 to September 2007 as input, three tests were designed and deployed: (1) Constructed for 59,839 pieces of cross-sectional data Test the feasibility of the compensation model based on EM clustering-BP neural network; (2) test the effectiveness of compensation accuracy for 59839 cross-sectional data under different missing ratios; (3) test the validity of the compensation model for 59839 cross-sectional data The validity test of the compensation accuracy of the compensation algorithm based on SVR and EM clustering-BP neural network.

[0053] The above three tes...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a biomedicine missing data compensation method based on an EM cluster-BP neural network and belongs to the technical field of biomedicine. According to the method, an iterative algorithm EM algorithm which is important in processing incomplete data problems is adopted, different missing data are partitioned in different clusters according to an EM cluster and primary compensation is completed; and models are established for complete data in each cluster through a BP neural network method and precise compensation of the missing data in each cluster is finished. According to the biomedicine missing data compensation method, adaptability of a compensation algorithm to any missing mechanism is enhanced to a certain degree, accuracy of compensation is improved and the method is suitable for the biomedicine missing data compensation field.

Description

technical field [0001] The invention relates to a method for supplementing biomedical vacant data, which belongs to the technical field of biomedicine. Background technique [0002] In recent years, with the continuous development of computer science and technology, data mining technology has been widely used in various fields. The overall process of data mining includes problem understanding, data acquisition and understanding, preprocessing, data mining, model evaluation, and knowledge application. The success and applicability of data mining depend to a large extent on data quality. However, in the process of mining biomedical data, the phenomenon of incomplete data is inevitable, and there are different degrees of vacant data, also known as vacant values. In order to effectively apply data mining methods and systems in the field of biomedical research, we must face the challenge of incomplete data. [0003] For the field of biomedical research, there are many reasons f...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06N3/08
Inventor 罗森林韩龙飞潘丽敏张铁梅
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com