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Drug recommendation algorithm based on depth learning

A deep learning and recommendation algorithm technology, applied in computing, informatics, medical informatics, etc., can solve the problem of users' lack of expert guidance

Inactive Publication Date: 2017-08-25
广东亿荣电子商务有限公司 +1
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention builds a model of the corresponding relationship between drug curative effect and disease under the deep learning framework, and proposes a personalized drug recommendation algorithm based on the model, which better solves the problem that users lack expert guidance for drug purchase

Method used

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  • Drug recommendation algorithm based on depth learning
  • Drug recommendation algorithm based on depth learning

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Embodiment Construction

[0014] The implementation framework of data acquisition and feature training of the present invention is as follows: figure 1 As shown, first collect the authoritative data of drug information such as CFDA and FDA and the drug sales information of the online shopping mall, build a self-encoded deep learning network, and use the collected data to train to obtain network weights. In the personalized recommendation process such as figure 2 As shown in Fig. 1, input relevant personal information and disease conditions into the trained network to obtain systematic personalized drug recommendations.

[0015] The specific implementation process of drug information collection and drug characteristic training:

[0016] 1. Obtain the name of the drug, the name of the disease to be treated, the dosage of the drug, side effects, and the chemical structure of the drug from the CFDA website;

[0017] 2. Collect disease information from data sources including the UMLS database;

[0018] ...

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Abstract

The present invention provides a drug recommendation algorithm based on depth learning. The present invention belongs to the field of computer software. a model of correspondence between drug effects and diseases is constructed in a framework of depth learning, and based on the mode, a personalized drug recommendation algorithm is proposed. The recommendation algorithm provided by the present invention comprises three parts: first, a drug-related information acquisition process, which comprises acquiring a name of an approved drug as well as a disease treated thereby, a side effect of the drug, precautions for use and other information from CFDA, and acquiring information such as sales data, user comments and price of the drug from an online drug mall; next, a depth learning feature training process, which comprises construction of a training network based on depth learning, a feature parameter training process, and output of drug classification information; and finally, individual recommendation, which comprises drug recommendation based on long-term personal health features and an implementation process thereof. The algorithm provided by the present invention better solves the problem that users lack instructions on drug purchasing from experts.

Description

technical field [0001] The present invention belongs to the technical field of computer software. [0002] technical background [0003] With the continuous development of information technology, more and more researchers are beginning to try to apply the most advanced technology to the field of medical and health care. There are more and more online pharmacies in foreign countries, and there are also online pharmacies such as Rongyao Online and Golden Elephant Pharmacy in China, which are receiving more and more attention. Buying medicines online is not limited by time, space, or region, and it is especially convenient for people who are busy or unable to exercise for a long time; in addition, a large amount of information on medicines, prices, and user reviews can be obtained online Buy medicines that are not available in the local area; and because online pharmacies save a series of expenses such as renting stores, employees, and storage, their prices are generally cheape...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G06Q30/06
CPCG06Q30/0631G16H50/20
Inventor 罗日红蔡君
Owner 广东亿荣电子商务有限公司
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