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

Disease classification model training method and device, storage medium and electronic device

A classification model and training method technology, which is applied in text database clustering/classification, special data processing application, unstructured text data retrieval, etc., can solve the problem of low efficiency of patient disease classification, and achieve the effect of accurate classification

Pending Publication Date: 2022-03-01
SHENZHEN UNISOUND INFORMATION TECH CO LTD
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a disease classification model training method, device, storage medium, and electronic device to at least solve the problem of low efficiency in classifying patient diseases in the prior art

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
  • Disease classification model training method and device, storage medium and electronic device
  • Disease classification model training method and device, storage medium and electronic device
  • Disease classification model training method and device, storage medium and electronic device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0029] It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate ...

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 disease classification model training method and device, a storage medium and an electronic device. The disease category classification model training method comprises the steps that treatment information of a disease sample user is acquired, and the treatment information comprises diagnosis information of different medical personnel on the sample user; a first feature is extracted from the doctor seeing information through a natural speech processing technology, a preset disease classification model is trained, a target disease classification model used for disease classification is obtained, the target disease classification model comprises a disease classification rule, and a first feature is extracted from the doctor seeing information; that is to say, the disease species of the patient can be quickly and accurately classified through the trained disease species classification model, and the technical problem of low classification efficiency of the disease species of the patient in the prior art is solved.

Description

technical field [0001] The present invention relates to the related fields of case information processing, in particular, to a disease classification model training method, device, storage medium and electronic device. Background technique [0002] In order to improve the refinement and scientific level of medical quality management, the National Health and Medical Commission has formulated 51 diseases that need to be monitored. Each hospital needs to report patients who meet the characteristics of these diseases to the national platform. [0003] The reporting personnel need to be fully familiar with the rules for classifying patients into 51 types of diseases and all the medical record information of patients, and then judge the diseases they belong to, and ensure that the diseases of patients are assigned correctly. [0004] For the above problems, no effective solution has been proposed yet. Contents of the invention [0005] Embodiments of the present invention provi...

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): G06F16/35G06F16/36
CPCG06F16/353G06F16/367
Inventor 饶显李霄寒
Owner SHENZHEN UNISOUND INFORMATION TECH CO LTD
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