关键词: 深度学习, 拓扑特征, 生存预测

Abstract: Lung cancer is one of serious diseases causing death for humans. Improving survival prediction performance is meaningful for making the treatment plans and improving the survival rates of lung cancer patients. In this paper, the survival prediction framework is based on histopathology images. In the proposed framework, it firstly detects the lung cancer cells automatically using deep learning method and then extracts features from the detected cells. The topological features are employed to describe the distribution of the cells and the topological features are used as the prediction factors for the survival prediction. Finally, the survival prediction is done by applying cox proportional hazards model with Lasso method. Experimental results show that the proposed method can improve both the efficiency and accuracy of cells detection and the power of lung cancer survival prediction model.

Key words: deep learning, topological features, survival prediction