The comparative study between ELM and SVM on predicting the postoperative survival time of NSCLC patients

At the present time, there has not been an effective model in medical field to predict the survival time of the non-small cell lung cancer patients after radical surgery. In this paper, we apply the Extreme Learning Machine (ELM) and Support Vector Machine (SVM) to forecast the survival time. Through experiment, the prediction exactitude of ELM and SVM can go up to 79.2% and 74.1%, respectively. It is proved that these two methods can obtain good effects. The comparison between ELM and SVM on predicting the postoperative survival time of the non-small cell lung cancer patients throws light on how to select an effective model to predict.