Multi-granularity breast cancer gene classification method based on dual adaptive neighborhood radius

An adaptive neighborhood and classification method technology, applied in the field of medical information intelligent processing, can solve the problems of the influence of high dimensionality of genetic data on the early detection of breast cancer and the difficulty of selecting the neighborhood radius of the neighborhood rough set, so as to improve the detection accuracy , reduce complexity, reduce the effect of judgment difficulty

Active Publication Date: 2021-12-24
NANTONG UNIVERSITY
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Problems solved by technology

[0006] The purpose of the present invention is to provide a multi-granularity breast cancer gene classification method based on double adaptive neighborhood radius, which solves the problem that the existing effective way to judge the status of breast cancer is that the dimension of breast cancer-related gene data is too high to be observed. The influence of ge

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  • Multi-granularity breast cancer gene classification method based on dual adaptive neighborhood radius
  • Multi-granularity breast cancer gene classification method based on dual adaptive neighborhood radius
  • Multi-granularity breast cancer gene classification method based on dual adaptive neighborhood radius

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Embodiment 1

[0076] see Figure 1 to Figure 5 , the present invention provides its technical scheme as, the multi-granularity breast cancer gene classification method based on double self-adaptive neighborhood radius, comprises the following steps:

[0077] Step 1: Read the breast cancer gene data set, convert the data into a quadruple decision information system S=(U,AT,V,f,δ), and the neighborhood decision information system S is expressed as follows:

[0078] S=(U,AT,V,f,δ), where U={x 1 ,x 2 ,x 3 ,...x m} represents the detection patient object set in the breast cancer gene data set, and m represents the number of breast cancer gene detection patients; C={a 1 , a 2 ,...,a n} represents a non-empty finite set of breast cancer gene features, n represents the number of breast cancer gene features; D={D 1 ,D 2} represents a non-empty finite set of category labels of breast cancer gene detection patients, AT=C∪D represents all gene attributes and decision attributes, d 1 Indicates ...

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Abstract

The invention provides a multi-granularity breast cancer gene classification method based on dual adaptive neighborhood radiuses, and the method comprises the following steps: reading large-scale gene locus data, carrying out normalization processing, and carrying out data analysis on large-scale gene loci; combining a contour coefficient and PCA dimension reduction visualization, selecting an optimal K value, and adjusting an information granulation model; realizing the multi-granularity attribute reduction based on cluster center distance adaptive neighborhood radius and multi-granularity attribute reduction based on neighborhood radius of attribute inclusion degree by using a heuristic reduction algorithm, and classifying and predicting breast cancer gene big data are classified and predicted by adopting an SVM machine learning classification algorithm. The invention has the beneficial effects that the penalty term is adjusted, so that the model has higher accuracy and recall rate in breast cancer gene classification, redundant attributes in large-scale data are removed, the calculation efficiency is improved, and the efficiency and precision of breast cancer data classification are improved by utilizing support information between samples.

Description

technical field [0001] The invention relates to the technical field of medical information intelligent processing, in particular to a multi-granularity breast cancer gene classification method based on double adaptive neighborhood radius. Background technique [0002] Cancer is one of the most common genetic diseases. Relevant medical studies have shown that lung cancer, skin cancer and breast cancer are closely related to genes. The appearance of cancer can often be explained by gene mutations. If the genetic material is damaged and not repaired, cancer cells will absorb it. The infinite division of nutrients of normal cells leads to the decline of human body functions. The cure rate of early cancer is high, and the cure rate of cancer cells after metastasis is low. Early detection and early treatment are the best treatment methods at present. Genetic testing is a non-destructive testing method. Simultaneous detection of thousands of gene loci through next-generation sequen...

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Application Information

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IPC IPC(8): G16B40/20G06K9/62G16H50/20G16H50/70
CPCG16B40/20G16H50/20G16H50/70G06F18/23213G06F18/2411G16B20/00
Inventor 丁卫平耿宇鞠恒荣黄嘉爽程纯孙颖张毅李铭秦廷桢沈鑫杰王海鹏
Owner NANTONG UNIVERSITY
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