Abstract
In recent years, the booming development of big data, cloud computing, Internet of Things, and other technologies provides conditions for the popularization and application of smart city. The combination of big data and medical information produces the emerging field of WITMED (Wise Information Technology of Med). WITMED is essential for the prospering growth of smart cities, which assumed a high quality of medical service is the most challenging goal for the city government. In this paper, the main attention is paid to the method of targeted gene therapy, which provides a new method for the treatment of oral cancer in inhibiting the growth, differentiation, invasion, and metastasis of oral cancer cells; therefore, the physical and psychological adverse effects of surgery and chemotherapy on patients are reduced and the survival and prognosis of patients are improved. Targeted gene therapy methods need to select the appropriate gene; that is, data mining methods are used to analyze a large number of complex genetic data from smart cities to obtain appropriate genetic markers, which makes the effect of targeted gene therapy better, and also provide some reference for the research of oral cancer gene direction and provide some basis for clinical treatment.
Highlights
Smart city is the use of advanced information technology to realize the intelligent management and operation of the city and create a better life for the people in the city and promote the harmonious and sustainable growth of the city
STRING genetic function analysis and literature review were used to further verify that the genes screened by us are closely related to the prognosis of oral cancer, which can provide a certain reference and theoretical basis for the future clinical research, treatment, diagnosis, and prognosis of oral cancer based on molecular biology
E survival curve, ROC curve, and AUC value were used to verify the results of the LASSO regression algorithm, and the results are shown in Figure 8. e second validation set was from NCBI, and the data of 74 oral cancer samples were sorted. e survival curve, ROC curve, and AUC value were used to verify the results of the LASSO regression algorithm, and the results are shown in Figure 9. erefore, it could be seen that these genes screened by LASSO regression analysis still have good results on other independent data sets and can better distinguish high-risk and low-risk patients with oral cancer
Summary
Smart city is the use of advanced information technology to realize the intelligent management and operation of the city and create a better life for the people in the city and promote the harmonious and sustainable growth of the city. In South Asia, the incidence and mortality rates of oral cancer and oropharyngeal cancer is the highest in Bangladesh. Predictive analytics rely on historical data and utilize advanced statistical or machine learning techniques to simulate the behavior or pattern so that it is possible to predict the likelihood of possible future trends or patterns in data. Operator (LASSO) regression analysis were used to conduct data mining analysis on the genetic expression of oral cancer patients, and risk genes that have an impact on the prognosis of oral cancer are screened out. STRING genetic function analysis and literature review were used to further verify that the genes screened by us are closely related to the prognosis of oral cancer, which can provide a certain reference and theoretical basis for the future clinical research, treatment, diagnosis, and prognosis of oral cancer based on molecular biology.
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