Correlation Analysis Between TCM Syndromes And Multi-factorial Pathogenesis In Colorectal Cancer

Colorectal cancer is one of the highest malignant tumors in the oncology department.It has two kinds of colon cancer and rectal cancer.WHO(World Health Organization)(2015)(2015)published survey results show that colorectal cancer in colorectal cancer worldwide in 2015 has about 774 thousand human deaths,and it is imminent to find effective methods for the treatment of colorectal cancer.The effective way to treat colorectal cancer is to perform surgical resection of the tumor site and assist in the radiotherapy and chemotherapy of the body.However,the toxic and side effects of these two methods have a great influence on the treatment effect and health of the patients.Therefore,it is imperative to find a new way to treat colorectal cancer.Investigation shows that the use of traditional Chinese medicine in the treatment of colorectal cancer is very effective.The key of traditional Chinese medicine to treat large intestine cancer is syndrome differentiation and treatment.However,there is no complete and scientific standard on the correlation between the syndrome of large intestine cancer and the pathogenesis of colorectal cancer.With the increase of the incidence of large intestine cancer,the correlation of the syndrome of large intestine cancer and the pathogenesis of colorectal cancer is becoming more and more important.In this paper,the data of the cases of large intestine cancer were analyzed by syndrome differentiation and quantification,and the data mining and traditional Chinese medicine were linked to achieve the standardized and standardized effect of traditional Chinese medicine.In this paper,data mining technology is used to classify three cases of colorectal cancer cases.1.,using stochastic forest model and establishing syndrome analysis model,we explore the correlation between syndromes and pathogenesis.The syndrome analysis model is designed to analyze the relationship between the syndrome and the pathogenesis of the disease,and provide the empirical basis for the doctor's treatment,which means that the disease machine can assist the doctor to determine which kind of syndrome.2.using random forests and recurrent neural network to build a TCM syndrome classification model for colorectal cancer.The classification effect of classification model before and after feature optimization is compared,and a model classification strategy is obtained.The experimental results show that the classification results of auxiliary diagnostic models will be improved to a certain extent after eliminating the irrelevant or weakly related pathogenesis characteristics.3.an improved RNN model(trick RNN)is proposed.TRNN technology based on matrix factorization reduces the number of training parameters of RNN model.Through two sets of experiments,it is found that the proposed tRNN model can approximate the effect of the original model RNN and accelerate the convergence speed.