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Approved research

Prediction of cancer occurrence and survival time based on deep learning method!eg:CNN! using gene and image data

Principal Investigator: Professor ZhangSheng Yu
Approved Research ID: 47192
Approval date: January 31st 2020

Lay summary

Question: At this stage, both image data and genetic data are used in the prediction of disease prediction and survival time, but how to combine the two for analysis is still to be studied. We want to use the relevant data in your database to analyze disease diagnosis and survival time prediction using convolutional neural networks. Aim: To select liver angiography data and genetic data, and to integrate two-part data training learning system by convolutional neural network, to learn the prediction model of liver disease and the model of survival time prediction, to provide relevant basis for doctor diagnosis, and to make up for the lack of research. It provides assistance for the diagnosis of cancer patients, increases the efficiency of doctors' work, increases the probability of disease discovery, increases the survival rate, and predicts the survival time of patients, so as to provide better follow-up treatment and services.