Research On Personalized Emergency Recuperation Technology Based On Deep Learning

Sanatorium is an indispensable part of military medical support chain,which takes responsibilities of prevention and healthcare,functional rehabilitation,as well as health appraisal and medical training for staff of special services.According to different division standards,recuperation consists of a variety of methods,and special service recuperation is an important one of them.Special recuperation service aims to serve people who are on special duty or engaged in special occupation.As these staff are the target person of our military personnel institution,this paper tries to investigate the methods of special service recuperation for these staff.However,traditional recuperation has not taken into account the individualized needs of the special staff,and the quality of convalescence and the effect of convalescence need to be improved.Based on the real data collected from a sanatorium,this paper adopts the deep learning technology to dig out the personalized chemotherapy needs and the best recuperation plan for different types of secret service personnel.In view of the heterogeneity,distribution and complexity of recuperation data,this paper builds a convalescent data set suitable for data analysis and mining after data integration and preprocessing.After that,a recommendation model of personalized special service recuperation program is built based on deep neural network.The model is based on the basic information and recuperation scheme of special service personnel,and is marked by convalescence results.After optimization and training,the prediction accuracy of the model reaches 92.5%,indicating that the accuracy of the model is ideal and has good application value.Finally,based on this model,we design and implement a customized personalized service system for recuperation.This system can recommend specific personalized chemotherapy regimen for different characteristics of special service personnel.After actual application,the system achieves good results.This paper has conducted both theoretical researches and practical applications for development of personalized special recuperation scheme,which provide a new way to solving the existing problems in the field of nursing service.These techniques can not only promote improvement of new technology research and application of data mining in nursing industry,but also to improve the utilization rate,expand nursing service function,develop health policy,and rational allocation of medical resources.