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Drug disease correlation analysis method based on time factor

A technology of correlation analysis and time factor, applied in the application field of complex network in disease analysis, to achieve good promotion and application value and increase the effect of accuracy

Pending Publication Date: 2019-11-26
山东健康医疗大数据有限公司
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Problems solved by technology

However, this method ignores the individual factors of real-world patients, especially the time of disease onset and medication time.

Method used

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  • Drug disease correlation analysis method based on time factor
  • Drug disease correlation analysis method based on time factor
  • Drug disease correlation analysis method based on time factor

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Embodiment

[0033] The drug-disease correlation analysis method based on time factors of the present invention, first of all, uses the number of patients as the weight to represent the drug-disease correlation to make up for the lack of individual factors in complex networks in the study of disease-drug correlation. Secondly, the method explores the positive and negative correlation between drugs and diseases under real-world data conditions through the analysis of patients' medication time and diagnosis time

[0034] The specific embodiments of the present invention will be described below based on the python language.

[0035] Such as figure 1 As shown, the drug-disease correlation analysis method based on time factors specifically includes the following steps:

[0036] S1. Drug-disease correlation discovery.

[0037] S11. Establish a complex network: establish a network with drugs, diseases, and patients as nodes. The relationship content of the network established by drugs, diseases...

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Abstract

The invention discloses a drug disease correlation analysis method based on time factors, and belongs to the technical field of application of complex networks in disease analysis. The drug disease correlation analysis method based on the time factor comprises: firstly, taking the number of the patients as the weight to measure the correlation between the drug and the disease, and then obtaining the positive and negative correlation between the drug and the disease by analyzing the drug use time and the diagnosis time of the patients. The drug disease correlation analysis method based on the time factor can make up for the defects in disease and drug correlation research, provides a direction for experimental research of research after drugs come into the market, and has good popularization and application value.

Description

technical field [0001] The invention relates to the technical field of application of complex networks in disease analysis, and specifically provides a method for analyzing drug-disease correlation based on time factors. Background technique [0002] At present, there are two main ways to study drugs and diseases. The first way is the way of clinical trials, which requires researchers to experiment repeatedly. This not only requires a lot of manpower and material resources, but is also very time-consuming. Generally, it takes 10 to 15 years for a drug to go from research to use [1]. Another way is to use various data mining techniques to study the correlation between drugs and diseases based on real-world data. With the rapid development of computer hardware, theoretical research on complex networks, machine learning, and neural networks has become more and more complete, and has become more and more popular in the medical field. Among them, complex network research is o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G16B45/00G16H70/40G16H70/60
CPCG16H70/40G16H70/60G16B45/00G06F18/23213G06F18/214
Inventor 刘文丽
Owner 山东健康医疗大数据有限公司
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