Research On Precision Medicine Application Based On Big Data Analysis Technology

Precision medicine is a new medical model based on the results of the "Human Genome Project" proposed by US President Barack Obama in his 2015 State of the Union address,and under the background of the rapid development of modern gene sequencing,bioinformatics and big data integration.Its essential core is personalized medicine as a starting point,which is a new approach to disease prevention and treatment,including differences in living environment and corresponding lifestyles.With the rise of correct medical planning in the world,in March 2016,the Ministry of Science and Technology,PRC held the first expert meeting on accurate medical strategy,and accurately pointed out China’s medical plan.It clearly pointed out that by 2030,the central government will invest 20 billion yuan,and local finance and enterprises will invest 40 billion yuan.The precision Medicine Plan in the medical field has incorporated the 14th Five-Year Plan into the major special research and development plan for scientific and technological development,so as to promote the building of a healthy China and improve the health of the people.The report to the 19th CPC National Congress identified "implementing the Healthy China Strategy" as an important part of the country’s basic development strategy,established a basic medical and health care system with Chinese characteristics,and specified the main goals of building a high-quality and efficient medical and health service system and effective prevention and control of major diseases.Implementing the Precision Medicine Plan will become an important part of China’s strategy to lead the implementation and development of a healthy China.At present,a prominent problem in the process of cancer treatment in China is that many patients have reached the final stage of disease development by the time they are discovered,losing the best treatment opportunity.It has been reported that 85 percent of cancer patients in the United States live for five years.In China,the figure is just 25 per cent.In the field of tumor prevention,the innovative development of public health and health care has been fully valued.It has received tumor prevention and treatment in the country,and has been increasing its investment.It is now receiving the right medical attention and can be prevented by early detection of the "clues" of malignant tumours in the environment.In addition to treatment,the quality of life and survival time of patients can be effectively improved.Therefore,it has become an urgent problem to improve the early diagnosis and precision medicine technology of cancer in China.Based on this,this thesis explores the influence of precision medicine on tumor patients and the prediction of tumor diseases under the big data.This thesis firstly integrates the researches on big data and precision medicine at home and abroad to serve as the theoretical basis of this study.Then,the definition and application of precision medicine and the difficulties affecting the overall layout of precision medicine were analyzed,and the actual impact of precision medicine on tumor patient groups was discussed.Then,on this basis,the research hypothesis of this thesis is put forward.The data of cancer patients released by the National Bureau of Statistics from 2010 to 2021 are selected as the research samples of this study,and the model is constructed using the model method described in Chapter 3.After the completion of model construction,in order to further test the superiority of GBRT model and actual analysis results,decision tree,logistic regression,random forest,etc.were selected to conduct comprehensive data inspection,and comprehensive analysis was carried out on sensitivity,accuracy,Matthew correlation coefficient,area of accurate recovery curve and area of receiver action characteristic curve,etc.It is concluded that the GBRT model selected in this thesis has the best prediction results for tumor cells.Then,the GBRT model selected in this thesis is further compared with the machine tool,and it is found that the overall accuracy and detection rate of the tool selected in this thesis is higher.Then,the prediction analysis of liver cancer was carried out,and the liver cancer data on the big data website was selected as the research object.Finally,the accuracy of the prediction of liver cancer patients with GBRT model was higher,and the prediction performance was better than other models.Through this study,it can be found that the GBRT model proposed in this thesis is the best method to predict malignant and benign liver cancer.By selecting the right model for tumor screening and prediction,early treatment and prevention can be achieved in a timely manner,and the survival rate and quality of life of patients in the later period can be better improved.