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

Elderly cognitive function classification method based on random forest

A cognitive function and random forest technology, applied in the field of biomedicine, can solve the problems of inconvenient and imprecise classification methods of cognitive functions, and achieve the effect of easy collection, fine classification and simplified use

Inactive Publication Date: 2017-02-22
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF0 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the inconvenient and imprecise problems in the classification method of cognitive function of the elderly, and propose a classification method of cognitive function of the elderly based on random forest

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
  • Elderly cognitive function classification method based on random forest
  • Elderly cognitive function classification method based on random forest
  • Elderly cognitive function classification method based on random forest

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] 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.

[0039] The test data comes from the survey data of 13 hospitals located in 7 different provinces and cities from 2011 to 2012. There are a total of 9,503 pieces of data, and each piece of data has 482 dimensions, including 9 major aspects such as medical conditions, personal basic information, and cognitive functions. The samples were all elderly people over the age of 60.

[0040] The test process mainly includes four links, and all links are completed on the same computer, which is configured as: Intel dual-core CPU (main frequency 2.93GHz), 4GB memory, and windows7 operating system.

[0041] link one

[0042] This section details the extraction of key cognitive domains that affect the classification of cognitive functions in ...

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 an elderly cognitive function classification method based on a random forest and belongs to the technical field of biomedicine. The method disclosed by the invention comprises the following steps: dividing the elderly cognitive function into three types by adopting MMSE scale scores and education levels; extracting a key cognitive domain influencing elderly cognitive function category classification by utilizing a cognitive function score relative ratio calculation method and a Pearson linearly dependent coefficient calculation method; establishing a random forest regression model, calculating attribute significance scores of non-scale attributes, and extracting external related attributes influencing the elderly cognitive function category classification; finally, equalizing the sample set based on the extracted key cognitive domain and external related attributes by adopting an SMOTE up-sampling method, and establishing an elderly cognitive function classification model by utilizing the random forest method. Compared with a scale classification method, the method provided by the invention has the advantages that the adopted attributes are few and easy to collect, and the method has high convenience; compared with other machine learning algorithms, subdivision of the elderly cognitive function types is realized, and research of a method for performing targeted intervention on the elderly cognitive functions is facilitated.

Description

technical field [0001] The invention relates to a random forest-based cognitive function classification method for the elderly, which belongs to the technical field of biomedicine. Background technique [0002] In recent years, the number of elderly people in China has been increasing day by day, and China has entered an aging society. The health problems of the elderly have become an important concern of the social medical and security system. The physiological function of the human body will continue to decline with the aging process. When the physiological function declines to a certain extent, the elderly will lose their ability to take care of themselves. At this time, a lot of manpower and material resources are needed to ensure their life, which will affect the social medical care and security system. bring great pressure. Therefore, how to prolong the healthy living conditions of the elderly and ensure the self-care ability of the elderly has greater social benefit...

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): G06F19/00G06K9/62
CPCG16H50/30G06F18/241
Inventor 罗森林焦龙龙潘丽敏孙志鹏刘旭东高君丰
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