Application Research On Intervention Model Of Intestinal Flora Of Colorectal Cancer Based On Artificial Intelligence

The scientific research has proved that the internal environment state of intestinal microbiota in human body can effectively reflect the risk of some diseases,such as irritable bowel syndrome(IBS),colorectal cancer(CRC),diabetes mellitus(DM),obesity and so on.At present,the main problem of medical treatment is the uneven distribution of resources,at the same time,the processing efficiency of each link is relatively low.While the AI technology can help optimizing resource allocation,raising the efficiency of each link of medical treatment,and improving the diagnosis and treatment effect.At present,with the integration of AI technology and medical health field deepening,AI is not constantly improving the level of medical services,and also has outstanding performance in electronic medical records,medical image assisted diagnosis,drug R&D,medical robots,etc.However,there are few researches on the application of AI nutrition intervention of intestinal microbiota in colorectal cancer in the treatment of it.Based on K-Means++ algorithm,Apriori algorithm,and text matching in NPL,this paper established a index model through deep learning,and completed the study on the application research of the intervention model of intestinal microbiot of colorectal cancer based on AI.What has been done in this paper is as follows:1、Based on the Meta-Analysis of several related literatures,the most basic data group of intestinal microbiot in CRC patients were obtained in this paper,which provided the direction for the follow-up study.It also learned the basic data processing in data mining,which include data processing,data cleaning,etc.By analyzing the application of K-Means algorithm in medical data,it found that K-Means++ algorithm solved the problem that the number of clustering centers K,which needed to be given in advance.One problem was that most of the time,before using it,people didn’t know how many categories the research data set should be divided into,for in some practical applications,the result of K value could not be simply obtained.The another one problem was that different initial clustering centers may also get different clustering results,for the K-Means algorithm needed to determine the initial clustering center artificially.2、It improved the Apriori algorithm and got the improved Apriori algorithm which was suitable for medical rules.It also solved the problems of item location and association scale caused by the complex association rules of intestinal microbiot of CRC patients.In the way of support counting in Apriori algorithm,through learning a variety of ways,the best way Hash tree algorithm was proposed to solve the problem of ball support counting.It used the actual CRC patient cases to verify the improved Apriori algorithm,to evaluate the association rules,and proposed lift and IS metrics to evaluate the accuracy of association rules.It also put forward the solution of how to achieve clinical effect by association rules of intestinal microbiot of CRC patients,which needed to be tested with large medical datasets,and the grouping of items should be considered by medical experts.3、It proposed a nutrition intervention index model,which based on the deep learning.It solved the basic problem of the research model by using the classic deep learning and text matching in NPL,that was,to make the intervention scheme most reasonable.In order to perfect the association rules,through a large number of literature learning,it found that could use the Simhash algorithm and LSI model to improve the model mechanism.Through the AI in-depth learning,K-Means++lgorithm,improved Apriori algorithm,text matching in NPL and other methods were combined with training,and through the continuous modification,the relationship between pathological rules and intervention programs was more reasonable,and the preset research effect was achieved.That is,under the guidance of doctors,the data of suspected CRC patients were examined by PCR,and the intervention model of intestinal microbiot based on AI were used to get the perfect intervention plan,which improved the diagnosis efficiency and effect of doctors.