Drug association graph construction method based on network science and convolutional neural network

A technology of convolutional neural network and construction method, which is applied in drug reference, semantic tool creation, unstructured text data retrieval, etc., can solve the problem of not being able to visually display the main drug association map, and achieve the effect of efficient automatic extraction

Pending Publication Date: 2019-01-08
武汉海云健康科技股份有限公司
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Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention provides a method for constructing a drug association map based on network science and convolutional neural network, which solves the problem t...

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  • Drug association graph construction method based on network science and convolutional neural network

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Embodiment Construction

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0019] The embodiment of the present invention provides a technical solution: a method for constructing a drug association map based on network science and convolutional neural network, which specifically includes the following steps:

[0020] Step 1. Extract the features of the drug information, combine the initial drug classification given by the pharmacist, and construct the functional association network between drugs through the convolutional neural networ...

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Abstract

The invention discloses a drug association graph construction method based on network science and a convolutional neural network. The method includes the following steps that: feature extraction is performed on drug information, and a function association network between drugs is constructed through a convolutional neural network method on the basis of initial drug classifications given by pharmacists; a drug co-sale association network is constructed through a network science method on the basis of drug sales data; and the function association network and the drug co-sale association networkform a two-layer composite network, and comparison analysis is performed through the network science method, and a complete drug association graph is obtained; and the graph is visualized by means ofdimensionality reduction and graph embedding. With the drug association graph construction method based on the network science and the convolutional neural network of the invention, drug association relations can be automatically extracted from the drug sales data accurately and efficiently; and the association graph of drugs can be visually displayed, and users can know the drugs at a glance.

Description

technical field [0001] The invention relates to the field of medicine technology, in particular to a method for constructing a medicine association map based on network science and convolutional neural network. Background technique [0002] From the point of view of the object of use: it uses humans as the object of use to prevent, treat, and diagnose human diseases. Purposefully regulate human physiological functions, there are prescribed indications, usage and dosage requirements; from the perspective of usage: in addition to appearance, patients cannot recognize their inner quality, and many drugs need to be used under the guidance of doctors, not by patients' choice Decide. At the same time, various factors such as the method, quantity, and time of drug use largely determine the effect of its use. Misuse not only cannot "cure the disease", but may also "cause disease" and even endanger life safety. Therefore, medicine is a special commodity: type complexity: there are ...

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Application Information

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IPC IPC(8): G16H70/40G06F16/36
CPCG16H70/40
Inventor 黎云严钢沈章
Owner 武汉海云健康科技股份有限公司
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