Research on Analysis and Prediction of Elderly Medical Satisfaction Based on Convolutional Neural Network

Abstract

In order to adapt to the development of economic and social aging, solve the practical problem of incomplete medical security system in China, and provide higher quality medical services to more elderly people. In this paper, a comprehensive and effective survey and data collection on the status quo of medical services for the elderly were conducted by means of questionnaire survey, and an evaluation index system affecting the satisfaction with medical services for the elderly was established by using SERVQUAL model. On this basis, this paper will survey the one dimensional data into two dimensional data, taking advantage of computer vision in depth study using convolution neural network model to generate satisfaction evaluation system for the weight of each index, and then using the trained network model as an effective assessment tools, effective training sample sets of the sample satisfaction accurately forecast, forecast results to improve the elderly health work provides some feasible suggestions.