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Esophageal squamous carcinoma patient survival risk prediction method based on convolutional neural network

A technology of convolutional neural network and esophageal squamous cell carcinoma, which is applied in the field of survival risk prediction of patients with esophageal squamous cell carcinoma based on convolutional neural network, can solve the problems of poor prediction effect of the evaluation model, inability to help patients, and judgment of prognosis, and achieve good results. Judging the effect of the prognostic effect

Inactive Publication Date: 2021-07-09
ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY
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Problems solved by technology

[0005] Aiming at the deficiencies in the existing background technology, the present invention proposes a convolutional neural network-based survival risk prediction method for patients with esophageal squamous cell carcinoma, which solves the problem that the existing evaluation model has poor prediction effect and cannot help patients judge the prognosis effect. technical problem

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  • Esophageal squamous carcinoma patient survival risk prediction method based on convolutional neural network
  • Esophageal squamous carcinoma patient survival risk prediction method based on convolutional neural network
  • Esophageal squamous carcinoma patient survival risk prediction method based on convolutional neural network

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[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0041] like figure 1 As shown, the embodiment of the present invention provides a method for predicting the survival risk of patients with esophageal squamous cell carcinoma based on convolutional neural network, and the steps are as follows:

[0042]Step 1: Obtain M clinical phenotype indicators, survival information and survival status of patients with esophageal squamous cell carcinoma as the original data set; collect clinical data of patients with esophag...

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Abstract

The invention provides an esophageal squamous carcinoma patient survival risk prediction method based on a convolutional neural network. The method comprises the steps of: collecting M clinical phenotype indexes and survival information of esophageal squamous carcinoma patients as original data; performing research by using a Kaplan-Meier method and a log-rank method to obtain a relationship between clinical phenotype indexes and lifetime information of the esophageal cancer patients; analyzing clinical phenotype indexes influencing survival prognosis of the patients by using Univariate Cox hazard analysis; extracting clinical phenotype indexes with higher correlation with the survival risk of the patients through a Relief feature selection algorithm and Pearson correlation analysis; and finally, constructing a survival risk prediction model of the esophageal squamous carcinoma patients by using a convolutional neural network and using clinical phenotype indexes with higher correlation, and further judging the prognosis survival risk of the patients. According to the method, the postoperative survival condition of the esophageal squamous carcinoma patients is accurately predicted, the prognosis risk prediction capability is improved, and the prognosis risk prediction cost is reduced.

Description

technical field [0001] The invention relates to the technical field of cancer risk assessment, in particular to a convolutional neural network-based survival risk prediction method for patients with esophageal squamous cell carcinoma. Background technique [0002] Esophageal cancer is one of the major malignant tumors that threaten the health of all human beings. Its incidence rate ranks 8th among malignant tumors in the world, and its mortality rate ranks 6th. The number of people who die from esophageal cancer in the world exceeds 300,000 each year. Esophageal cancer is mainly Can be divided into esophageal adenocarcinoma and esophageal squamous cell carcinoma. Esophageal adenocarcinoma is mainly distributed in Europe and America, mainly in the United States, and esophageal squamous cell carcinoma is mainly distributed in Asia, mainly in China. my country is one of the regions with a high incidence of esophageal cancer in the world, and esophageal cancer has become an imp...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30G16H50/80G06N3/04G06N3/08
CPCG16H50/30G16H50/80G06N3/084G06N3/045G06N3/048
Inventor 王妍朱传迁王延峰凌丹张桢桢孙军伟王英聪姜素霞王立东赵学科
Owner ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY
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