Supercharge Your Innovation With Domain-Expert AI Agents!

An auxiliary device for diagnosis of Tibetan medicine based on multi-label learning

A diagnostic assistance, multi-label technology, applied in medical automation diagnosis, computer-aided medical procedures, informatics, etc., can solve the problems of low accuracy of diagnosis results, lack of objective interpretation of diagnosis results, etc., and achieve the effect of improving classification accuracy.

Active Publication Date: 2021-11-02
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] When traditional manual methods are used to predict Tibetan medicine treatment methods, it mainly relies on the personal experience of doctors, which leads to a decrease in the accuracy of the diagnosis results, and different doctors may obtain different treatment methods, and the diagnosis results obtained based on the personal experience of doctors lack objective interpretation.

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
  • An auxiliary device for diagnosis of Tibetan medicine based on multi-label learning
  • An auxiliary device for diagnosis of Tibetan medicine based on multi-label learning
  • An auxiliary device for diagnosis of Tibetan medicine based on multi-label learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0044] In order to facilitate understanding of the present invention, first the basic definitions involved in the present invention are described:

[0045] Symptoms: Refers to the symptoms of the disease. The clinical manifestations of the disease, such as sweating, dizziness, tinnitus, fever, etc., are the original basis for judging the disease;

[0046] Syndrome: It is a comprehensive analysis of various symptoms, and a pathological summary of the etiology, disease location, and nature of the disease at a certain stage during the occurrence and development of the disease;

[0047] Summary of Syndrome and Mechanism: It refers to a general summary of the etiology and pathogenesis. The etiology refers to the cause of a disease, and the pathogenesis refers to the mechanism of the occurrence, development, change and outcome of the disease;

[00...

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 belongs to the field of assistant decision-making of ethnic medicine, and specifically provides a Tibetan medicine diagnostic auxiliary device based on multi-label learning, which is used to solve some problems in the traditional Tibetan medicine legislation process: inaccuracy, difference, and lack of objectivity of diagnostic results Explanation, the present invention can provide auxiliary decision-making support for the diagnosis and treatment process of Tibetan medicine doctors, and it has the following advantages: 1) construction of feature view: dynamically update feature view through continuous iteration of training process; 2) label transfer: between 3 classifiers Pass the most reliable samples between pairs, optimize the classifier, and improve the classification accuracy; 3) Optimal classification result selection: use the combination of "vector splicing" and "weight assignment" to select the optimal prediction result.

Description

technical field [0001] The invention belongs to the field of auxiliary decision-making of ethnic medicine, and specifically relates to a Tibetan medical diagnosis auxiliary device based on multi-label learning. Background technique [0002] Tibetan medicine is an important part of the medical treasure house of the motherland. It has a long history of more than 3,000 years and has made great contributions to the reproduction and prosperity of the Tibetan nation and the entire Chinese nation. The scientific research and inheritance of Tibetan medicine have been valued. In clinical trials of Tibetan medicine, physicians mainly diagnose and treat patients according to the following three steps: 1) Syndrome differentiation: Physicians determine the patient's syndrome type according to the etiology and pathogenesis, 2) Legislation: determine the treatment method according to the patient's syndrome, 3) Prescription: Prescriptions are prescribed according to syndrome types and treat...

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 Patents(China)
IPC IPC(8): G16H50/20G06K9/62
CPCG16H50/20G06F18/24G06F18/214
Inventor 李巧勤巩小强刘勇国杨尚明
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com