Traditional Chinese medicine prescription relocation method based on heterogeneous network representation learning

A heterogeneous network and relocation technology, applied in neural learning methods, drugs or prescriptions, biological neural network models, etc., can solve the problem that the feature generation method cannot handle irrelevant or redundant generated features, and achieve the effect of avoiding domain knowledge.

Pending Publication Date: 2022-02-15
SOUTHEAST UNIV
View PDF0 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Purpose of the invention: The purpose of the present invention is to propose a Heterogeneous Network Pharmacology Learning for Prescriptions Repositioning of Traditional Chinese Medicin

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
  • Traditional Chinese medicine prescription relocation method based on heterogeneous network representation learning
  • Traditional Chinese medicine prescription relocation method based on heterogeneous network representation learning
  • Traditional Chinese medicine prescription relocation method based on heterogeneous network representation learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0046] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described below in conjunction with specific embodiments and accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and It is not intended to limit the invention.

[0047] A method for relocating traditional Chinese medicine prescriptions based on heterogeneous network representation learning of the present invention includes the following steps in sequence:

[0048] 1. Construction of a heterogeneous network of traditional Chinese medicine prescriptions:

[0049] The input data is preprocessed, including the representation of various entities and relationships, and the heterogeneous network G of Chinese medicine prescriptions is obtained after representation; the association of corresponding nodes in the connection network is establ...

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 discloses a traditional Chinese medicine prescription relocation method based on heterogeneous network representation learning. The method sequentially comprises the following steps: step 1, carrying out preprocessing on input data, and constructing a traditional Chinese medicine prescription heterogeneous network; step 2, according to a heterogeneous graph embedding method, learning semantic association information in the traditional Chinese medicine prescription heterogeneous network by executing a network pharmacology learning module, and acquiring embedded representations of the traditional Chinese medicine prescription and the disease; and step 3, according to the embedded representation of the traditional Chinese medicine prescription and the disease obtained in the step 2, using a deep learning recommendation algorithm to obtain an interactive influence score matrix of the two, and finally, sorting scoring matrix results to obtain a disease recommendation result of the Top@K of the traditional Chinese medicine prescription. According to the invention, the disease recommendation of the traditional Chinese medicine prescription can be obtained through intelligent calculation, manual operation is avoided, and the efficiency of traditional Chinese medicine prescription relocation is effectively improved.

Description

technical field [0001] The invention relates to a method for relocating traditional Chinese medicine prescriptions, in particular to a method for relocating traditional Chinese medicine prescriptions based on heterogeneous network representation learning. Background technique [0002] Drug repositioning aims to find new applications for existing drugs, and has the advantages of low waste rate, reduced cost and short time, which has attracted the attention of many researchers. Although there is a lot of research work on the repositioning of western medicines, in view of the characteristics of "multi-components, multi-targets, and multi-path regulation" in traditional Chinese medicine prescriptions, the repositioning method of western medicines cannot be directly applied to the repositioning of traditional Chinese medicine prescriptions. In addition, although some scholars have used network pharmacology to study the relocation of traditional Chinese medicine prescriptions, the...

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
IPC IPC(8): G16H20/10G16H50/70G06N3/08
CPCG16H20/10G06N3/08G16H50/70
Inventor 何洁月朱润宋凌宁
Owner SOUTHEAST UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap