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A disease factor data processing method and system

A data processing and factoring technology, which is applied in the fields of electrical digital data processing, special data processing applications, and medical data mining.

Active Publication Date: 2017-04-12
BEIJING QUALITY & ZEAL INFORMATION TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The existing correlation analysis method for patient information divides the patient's disease factors and only conducts a simple test

Method used

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  • A disease factor data processing method and system
  • A disease factor data processing method and system
  • A disease factor data processing method and system

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Embodiment Construction

[0011] Embodiments of the present invention will be described in more detail below in conjunction with the accompanying drawings.

[0012] Embodiments of the present invention are based on canonical correlation analysis. Before introducing the details of the embodiment of the present invention in detail, some concepts and steps of canonical correlation analysis are briefly described.

[0013] Canonical correlation analysis is a multivariate statistical analysis method that uses the correlation between comprehensive variable pairs to reflect the overall correlation between two groups of indicators. Its basic principle is: in order to grasp the correlation between the two groups of indicators as a whole, two representative comprehensive variables U1 and V1 are respectively extracted from the two groups of variables (respectively, the linear variables of each variable in the two variable groups Combination), using the correlation between these two comprehensive variables to refl...

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Abstract

The invention discloses a disease factor data processing method. The method comprises the steps that 1, patient disease factor data is converted into a disease factor matrix through normalization; 2, the patient disease factor data is divided into different disease factor sets, and different disease factor set matrixes are obtained from the matrix; 3, for the different disease factor set matrixes, a correlative coefficient among the disease factor sets is acquired through canonical correlation analysis, and correlative factor subsets among the disease factor sets are obtained; 4, significance computation is performed by using the correlation between the disease factor matrix and the obtained disease factor sets and the obtained correlative factor subsets to obtain the significance between every two disease factor set matrixes in the different disease factor set matrixes; 5, correlative factor sets and correlative factors among the factor sets are obtained through the significance and the correlative coefficient.

Description

technical field [0001] The present application relates to the field of medical data mining, and more specifically relates to a method and system for mining object-factor relationship based on canonical correlation analysis. Background technique [0002] In the process of disease discovery and treatment, corresponding diagnosis is usually made based on different information of patients, so the accuracy of different information and its correlation is very important for disease diagnosis. The existing correlation analysis method for patient information divides the patient's disease factors and only conducts a simple test. Therefore, a new method capable of analyzing different disease factors of a patient as a whole is expected. Contents of the invention [0003] In order to solve the above-mentioned problems existing in the prior art, one aspect of the present invention proposes a method for processing disease factor data, the method comprising: Step S1: transforming the dis...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00
CPCG16H50/70
Inventor 黄亦谦
Owner BEIJING QUALITY & ZEAL INFORMATION TECH CO LTD
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