Login| Sign Up| Help| Contact|

Patent Searching and Data


Title:
TRIAGE FUSION MODEL TRAINING METHOD, TRIAGE METHOD, APPARATUS, DEVICE, AND MEDIUM
Document Type and Number:
WIPO Patent Application WO/2021/164388
Kind Code:
A1
Abstract:
The present application relates to the field of big data processing. Provided is a triage fusion model training method, a triage method, an apparatus, a device and a medium. The method comprises: obtaining a treatment sample set; inputting said treatment samples into a multi-fusion neural network model containing initial parameters; performing prediction with respect to the treatment samples and obtaining at least two triage results; performing standardization conversion on each triage result to obtain standardized results; performing weight fusion on all standardized results to obtain sample triage results; obtaining, by means of loss modeling in the multi-fusion neural network model, a total loss value; if the total loss value has not reached a preset convergence condition, iteratively refreshing the initial parameters of the multi-fusion neural network model until convergence, then recording the post-convergence multi-fusion neural network model as a triage fusion model. The present method improves performance and accuracy of multi-fusion neural network model identification. The present application is applicable to the fields of smart medical care, etc., and can further promote the development of smart cities.

Inventors:
TANG RUI (CN)
LI YANXUAN (CN)
ZHU ZHAOWEI (CN)
SUN XINGZHI (CN)
Application Number:
PCT/CN2020/135343
Publication Date:
August 26, 2021
Filing Date:
December 10, 2020
Export Citation:
Click for automatic bibliography generation   Help
Assignee:
PING AN TECH SHENZHEN CO LTD (CN)
International Classes:
G06N3/08; G16H40/20
Foreign References:
CN110047584A2019-07-23
CN110347838A2019-10-18
CN106202847A2016-12-07
CN111553399A2020-08-18
CN111477310A2020-07-31
US20190279767A12019-09-12
Attorney, Agent or Firm:
SHENZHEN ZHONGDING INTELLECTUAL PROPERTY AGENCY (CN)
Download PDF: