A non-small cell lung cancer prognosis survival prediction method, a medium and an electronic device. The method comprises: acquiring a CT image to be subjected on prediction, performing grayscale normalization processing on the CT image to be subjected on prediction, and extracting a region of interest; on the basis of the region of interest, using a trained prognosis survival model based on deep learning to predict and obtain a corresponding prognosis survival time classification result, wherein the prognosis survival model based on deep learning is a deep learning convolutional neural network model, and comprises five convolutional blocks, one fully connected layer and one classification layer; and extracting tumor abstract features layer by layer, and obtaining a prognosis survival time classification result, wherein among the five convolutional blocks, a Bottleneck architecture is introduced into three convolutional blocks in the middle, and a fusion layer is added to the last convolutional block on the basis of the Bottleneck architecture.
NON-SMALL CELL LUNG CANCER PROGNOSIS SURVIVAL PREDICTION METHOD, MEDIUM AND ELECTRONIC DEVICE