Classification prediction method and device based on data fusion and storage medium

A technology of classification prediction and data fusion, applied in the field of pattern recognition, it can solve the problems of different X-ray image understanding, time-consuming and labor-intensive diagnosis process, and different diagnosis results, achieving excellent stability and accuracy. Effect

Pending Publication Date: 2020-04-17
FOSHAN UNIVERSITY
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Problems solved by technology

The traditional diagnostic tests for breast cancer are fine-needle aspiration cytology (FNAC) and mammography, both of which have certain defects: FNAC analysis depends on the joint diagnosis of pathology, radiology and oncology experts, and

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  • Classification prediction method and device based on data fusion and storage medium
  • Classification prediction method and device based on data fusion and storage medium
  • Classification prediction method and device based on data fusion and storage medium

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[0037] The concept, specific structure and technical effects of the present disclosure will be clearly and completely described below in conjunction with the embodiments and drawings, so as to fully understand the purpose, scheme and effect of the present disclosure. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0038] refer to figure 1 ,like figure 1 Shown is a classification prediction method based on data fusion, including the following steps:

[0039] Step S100 , marking the collected sample data as malignant samples or benign samples, and constructing the marked sample data as a sample data set.

[0040] Wherein, the sample data is breast mass nucleus data; the breast mass nucleus data is used to describe the physical characteristics of the breast mass nucleus, for example, radius, texture, perimeter, area, compactness, degree of depression, number of...

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Abstract

The invention relates to the technical field of pattern recognition, in particular to a classification prediction method and device based on data fusion and a storage medium. The method comprises thesteps: firstly marking collected sample data as a malignant sample or a benign sample, and constructing a sample data set through the marked sample data, and the sample data is breast lump cell nucleus data; preprocessing and normalizing the sample data set to obtain a normalized data set, and dividing the normalized data set into a training set and a test set; adopting a plurality of neural networks to train a normalized data set, and integrated three networks through an AdaBoost algorithm to generate an integrated classifier; and finally, obtaining test data in real time, and inputting the test data into the integrated classifier to obtain a diagnosis result. The invention further provides a classification prediction device and a storage medium correspondingly, and a classification prediction effect with high stability and accuracy for breast tumors can be obtained.

Description

technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a classification prediction method, device and storage medium based on data fusion. Background technique [0002] Breast cancer is one of the leading causes of death in women worldwide. According to statistics, early and accurate breast cancer diagnosis can make more than 30% of breast cancer patients live longer. The traditional diagnostic tests for breast cancer are fine-needle aspiration cytology (FNAC) and mammography, both of which have certain defects: FNAC analysis depends on the joint diagnosis of pathology, radiology and oncology experts, and the diagnostic results may vary from person to person The diagnosis process is time-consuming and labor-intensive; the diagnosis based on X-ray technology also has the defect that the understanding of X-ray images varies from person to person. [0003] Therefore, how to provide a method for assisting professional medic...

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Application Information

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IPC IPC(8): G16H50/30G06K9/62
CPCG16H50/30G06F18/2148G06F18/241Y02A90/10
Inventor 刘静张志飞张君
Owner FOSHAN UNIVERSITY
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