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Decision-making model establishing method for auxiliary medical system

A decision-making model and method-building technology, which is applied in computer-aided medical procedures, medical automated diagnosis, biological neural network models, etc., can solve the problems of low maturity of decision-making models and achieve high accuracy and strong robustness

Pending Publication Date: 2020-08-21
CENT SOUTH UNIV
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AI Technical Summary

Problems solved by technology

However, the decision-making model of the existing auxiliary medical system is not mature enough, and the analysis results made deviate greatly from the actual situation

Method used

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  • Decision-making model establishing method for auxiliary medical system
  • Decision-making model establishing method for auxiliary medical system
  • Decision-making model establishing method for auxiliary medical system

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Embodiment Construction

[0039] refer to Figure 1-3 , a specific embodiment of the present invention includes the following steps,

[0040] A. Use the support vector machine to construct the first classifier, and use the directed acyclic graph support vector machine to construct the second classifier;

[0041] B. Use the neural network to supplement the support vector machine, so as to hedge the risk when the support vector machine makes an error;

[0042] C. Integrating support vector machines and neural networks through ensemble learning.

[0043] In step A,

[0044] Suppose the sample set is {(x 1 ,y 1 ), (x 2 ,y 2 ),..., (x n ,y n )}, x i ∈R d , the equation of the hyperplane is: ω T x+b=0, the optimization problem of support vector machine is equivalent to finding a set of suitable parameters (ω, b), so that the following equations are established,

[0045]

[0046] With the help of Lagrange function and dual problem, the above problem can be simplified into the following equation...

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Abstract

The invention discloses a decision model establishing method for an auxiliary medical system. The method comprises the following steps of: A, establishing a first classifier by using a support vectormachine, and establishing a second classifier by using a directed acyclic graph support vector machine; B, supplementing the support vector machine by using a neural network to realize elimination ofrisks in a manner of hedging when the support vector machines go wrong; and C, integrating the support vector machines and the neural network through ensemble learning. According to the invention, thedefects in the prior art can be overcome, and the accuracy of inspection data analysis is improved.

Description

technical field [0001] The invention belongs to the technical field of auxiliary medical equipment, in particular to a method for establishing a decision model for an auxiliary medical system. Background technique [0002] With the development of society, people pay more and more attention to their own health problems. As a large developing country, my country is currently rapidly entering an outbreak period of medical demand. my country's population has reached 1.45 billion, more than 5,600 people can share one doctor, and one doctor needs to treat 72 patients a day. In big cities, hospitals treat more than 1 million people every year on average, while hospitals with higher standards and richer medical resources have to accept more than 3.5 million people every year. And 80% of my country's medical resources are distributed in big cities and developed areas. The permanent population of these areas is about 3 million, accounting for only 7% of the total population. The r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G06K9/62G06N3/04
CPCG16H50/20G06N3/045G06F18/213G06F18/2411
Inventor 吴嘉庄庆贺陈焕泽谭延林田晓明
Owner CENT SOUTH UNIV
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