Research On The Construction And Application Of Personalized Medicine Recommendation Model Based On Differential Evolution Algorithm

As a key part of the popularization path of digital medicine and Internet medical treatment,personalized medicine is the core goal of fully realizing the standardized management and use of population health information in China,and meeting the needs of personalized services and precision medicine.And the development of personalized medicine is closely related to the evaluation of pharmacokinetic parameters and the fitting of blood drug concentrations.If only refer to foreign application guides and databases,unable to meet the application needs of Chinese people in an all-round way.Therefore,it is necessary to grasp the domestic advantages and establish a research system and mechanism for personalized medicine with Chinese characteristics.In addition,due to the particularity of the personalized medicine research system,only single-disciplinary research cannot meet the needs of technological progress,and multi-professional cross-research and multi-disciplinary cross-integration are needed to adapt to multi-faceted research.Therefore,based on the data of the Chinese population,this paper constructs a recommendation model and its application system for the whole process of personalized medicine,explores the regularity of cross modal data in personalized medicine,and enriches the research results of personalized medicine in China.Based on the actual situation in China,carry out research on the application of Chinese style personalized medicine use.On the one hand,China has a multi-ethnic background,which can provide rich sample gene and group resource information.On the other hand,China has a large number of absolute cases.Based on this advantage,this paper constructs an application and prediction system for personalized medicine,establish a full process personalized medicine assistant decision-making system.The following aspects are the main summary of this paper:The first part analyze the current situation of personalized medicine and personalized medicine prediction.The second part comprehensively describe the basic principles of personality pharmacokinetic parameters and group pharmacokinetic parameters.The third part builds a recommendation model for the prediction of personalized medicine.The fourth part analyzes the recommendation model of personalized medicine through empirical analysis.The fifth part combines the actual clinical needs and expounds the three application scenarios.The sixth part summarizes the research work of the full text and gives an outlook.The main innovations of this paper are as follows:First,in terms of model construction,this paper explores the framework of influencing factor mining and core parameter calculation in the whole process of personalized medicine recommendation.Second,in terms of model results verification,this paper optimizes the recommended model parameters by presetting the result accuracy and setting multiple iterations.Thirdly,in terms of model application,this paper presets the application scenarios,simulate the determination of personalized medicine administration scheme,individual pharmacokinetic parameters and adjustment of medicine administration scheme in clinical application.The research in this paper not only provides a new process and method reference for the development of personalized medicine research based on the Chinese population and the formation of an personalized medicine model,enriches the clinical practice in this field;but also has an important auxiliary reference role for doctors and pharmacists to comprehensively analyze the patient group,design and implement personalized precise dosing regimens.This is not only concentrate relevant resources and strength to shorten the gap,but also helps to build a new pattern of clinical personalized medicine research in China.