Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Clinical medication recommendation method based on multi-source heterogeneous data

A recommendation method and heterogeneous technology, applied in the fields of medical data mining, special data processing applications, drugs or prescriptions, etc., can solve the problems of data correlation and time series complexity, and achieve enhanced reliability and easy expansion and integration. Effect

Pending Publication Date: 2021-01-15
DALIAN UNIV OF TECH
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

And this kind of data has a certain degree of interrelationship and time series complexity

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
  • Clinical medication recommendation method based on multi-source heterogeneous data
  • Clinical medication recommendation method based on multi-source heterogeneous data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0015] like Figure 1-Figure 2 As shown, the present invention is a clinical drug recommendation method based on multi-source heterogeneous data, the multi-source heterogeneous data includes personal information data including patient age, gender, ethnicity and education, and main diagnostic information; wherein, the main Diagnostic information is regarded as static information, and the sequential inspection results and therapeutic drugs are regarded as heterogeneous sequence data; the intelligent recommendation method for clinical medication is to input the obtained multi-source heterogeneous data into the model fusion network and use deep learning Technical learning obtains comprehensive patient representation information, the specific steps are as follows:

[0016] S1. Through the dual-channel long-short-term memory network, respectively encode the experimental inspection sequence and the medication sequence to obtain the corresponding representation vector at each moment ...

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 clinical medication recommendation method based on multi-source heterogeneous data. The multi-source heterogeneous data comprises human information data including patient age, gender, ethnic group, education and main diagnosis information, wherein the main diagnosis information is regarded as static information, and the sequential examination result and the therapeutic drug are regarded as heterogeneous sequence data; according to the clinical medication intelligent recommendation method, obtained multi-source heterogeneous data is input into a model fusion network, and comprehensive patient representation information is obtained through learning by means of the deep learning technology.

Description

technical field [0001] The invention relates to the field of medical clinical medication methods, and more specifically, relates to a method for recommending clinical medication based on multi-source heterogeneous data. Background technique [0002] The clinical decision support system based on health care big data can provide medical workers, patients or any individual with knowledge, specific individual or group information, intelligently filter and express information, in order to provide better health, diagnosis and public health services to achieve the best clinical outcomes. As an important part of clinical decision-making, treatment and drug decision-making can assist doctors to more efficiently select and formulate the best treatment plan and drug combination that are beneficial to patients based on historical medical and health big data, so as to better alleviate the lack of medical resources. status quo. Medical big data has four big data characteristics: large a...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G16H20/10G16H50/70G06F16/9535G06K9/62G06N3/04
CPCG16H20/10G16H50/70G06F16/9535G06N3/044G06N3/045G06F18/25
Inventor 金博安洋魏小鹏
Owner DALIAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com