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A tumor molecular typing prediction system

A molecular typing and prediction system technology, applied in the field of data processing, can solve the problems of molecular typing of diseases that cannot be multi-category, troublesome parameter selection, and low classification accuracy, and achieve high tumor molecular typing prediction and rapid classification. The effect of accuracy

Active Publication Date: 2018-10-23
NORTHEASTERN UNIV LIAONING
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Problems solved by technology

Existing technical methods for tumor molecular typing, such as SVM and Logistic regression, have shortcomings such as slow speed, poor generalization performance, troublesome parameter selection, and low classification accuracy, and the traditional ELM (Extreme Learning Machine) method cannot Molecular typing of diseases in multiple categories, and is a supervised machine learning method

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Embodiment Construction

[0030] The specific implementation manners of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0031] A tumor molecular typing prediction system, such as figure 1 shown, including:

[0032] Gene expression data extraction module: obtain tumor gene expression data;

[0033] Missing value preprocessor: KNN algorithm is used to convert the tumor gene expression data containing missing values ​​into tumor gene expression data without missing values, and fill in missing values ​​for the acquired tumor gene expression data;

[0034] Use the nearest neighbor (k-Nearest Neighbor, KNN) filling method to fill the tumor gene expression data matrix with missing values Convert to tumor gene expression data matrix without missing values There are m patients, and each patient has n genes.

[0035] The filling method of KNN is to select the gene whose expression is most similar to the gene under study to estimate the missing value....

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Abstract

A tumor molecular classification prediction system, including: a gene expression data extraction module: to obtain tumor gene expression data; a missing value preprocessor: to fill in missing values ​​for the obtained tumor gene expression data; an important gene extraction module: to extract tumor gene expression data Important tumor genes that determine survival time; US-ELM molecular classification module: Use US-ELM to predict tumor molecular classification using important tumor gene data. The tumor molecular typing prediction system of the present invention overcomes the shortcomings of previous tumor molecular typing technical methods such as slow speed, poor generalization performance, and low classification accuracy, and achieves fast and high classification accuracy prediction of tumor molecular typing. , and can perform unsupervised machine learning on multiple categories of tumors. Using the system of the present invention to predict tumor molecular classification can better judge the biological behavior of tumors. The direct purpose of the present invention is not to obtain diagnostic results, but to provide a reference for formulating personalized treatment plans.

Description

technical field [0001] The technical field of data processing of the present invention, in particular relates to a tumor molecular typing prediction system. Background technique [0002] For a long time, judging the biological behavior of tumors, formulating treatment plans, and judging prognosis have largely relied on the histological typing and clinical staging of tumors. However, clinical practice has shown that even with tumors bearing the same histological morphology (including stage and grade), the clinical symptoms of different patients can be very different, and may have significantly different responses to the same treatment. In 1991, the National Institute of the United States proposed the concept of tumor molecular typing. Based on comprehensive molecular typing technology, the basis of tumor classification changed from morphology-based to molecular-based "molecular typing". [0003] The ultimate goal of tumor molecular typing is to clarify the molecular characte...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16H50/30G06F19/18
CPCG16H50/20
Inventor 王之琼刘馨遥李艳丽曲璐渲张锦辉赵越
Owner NORTHEASTERN UNIV LIAONING
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