Design and application of tumor prediction model based on statistical method*. (31st October 2017) - Shen, Shuting; Fan, Ziqiang; Guo, Qi
Abstract: Two prediction models for tumor prediction based on logistic regression and BP neural network were proposed in this paper; a sensitivity analysis of risk factors was also conducted. The two protocols will be implemented in the R language and demonstrated with relevant lung cancer data. Additionally, the two models are compared, verifying their accuracy and feasibility. Finally, a function is combined with R language, which can quickly achieve the above two programs. It is set up to obtain the tumor prediction model and the risk factors on the degree of correlation of the size of the disease. This method is convenient and practical and we hope it can be applied in the early discovery of cancer during future medicine.