Risk Evaluation And Prevention Of Parallel Breast Cancer System Based On Interval Type-2 Fuzzy Logic

Breast cancer is one of the five common malignant cancers in China,and women are the main incidence group,ranking the fifth in the cause of death of female malignant tumors.In recent years,with the incidence of breast cancer has risen sharply and become younger,seriously affecting women’s physical and mental health.Due to the low domestic per capita economic income and the large population base,a comprehensive breast cancer screening cannot be carried out.However,once breast cancer is diagnosed,it is often in the middle and advanced stage.On the other hand,the early screening and early prevention of breast cancer can effectively improve the survival rate of breast cancer patients.Therefore,find out the risk factors of breast cancer,thus establish the risk model of breast cancer,the evaluation results,and formulate corresponding prevention countermeasures,to reduce the risk of breast cancer and incidence,is of great significance to women prevention of breast cancer,help to improve their quality of life and life satisfaction.By integrating the interval type-2 fuzzy theory and ACP method(Artificial Systems,Computational Experiments,Parallel Execution),a risk assessment model was established according to the factors affecting women with breast cancer,and the corresponding prevention measures were given.Firstly,according to the statistical analysis of breast cancer patients and the diagnostic experience of clinicians,12 factors were determined as the index set of risk level,the influence of each factor on breast cancer was analyzed and the corresponding weight was determined.The interval type-2 fuzzy set {low,medium and high} was used to divide the risk level of each factor;Secondly,the membership function corresponding to the interval type-2 fuzzy set was established respectively,and the comprehensive evaluation method of interval type-2 fuzzy was used to assess the risk of women with breast cancer;Thirdly,according to the NICE(National Institute for Health and Care Excellence)guidelines for risk management related to breast cancer,doctors’ clinical experience and cancer risk level give corresponding measures to reduce the risk of cancer to prevent the occurrence of breast cancer;Finally,based on the interval type-2 fuzzy comprehensive evaluation model and combined with ACP method,a parallel breast cancer prevention system framework was established to realize the virtual and real interaction between the actual breast cancer prevention system and the artificial breast cancer prevention system,real-time monitoring of potential breast cancer patients’ physiological indicators,and active optimization of corresponding prevention strategies,so as to realize the normalization of physiological indicators of breast cancer patients with potential.In this paper,a breast cancer risk assessment model is established based on the interval type-2 fuzzy set and the two-level comprehensive evaluation method,and the corresponding fuzzy rules are given.According to the parallel system theory,the application effect of prevention programs is verified by computational experiments,and the intervention measures are actively optimized to form a real-time disease prevention system with virtual and real interaction.This method opens up new avenues for breast cancer prevention and is of great significance for reducing the incidence of breast cancer.