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
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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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