医学信息2024，Vol.37Issue(14)：25-32,8.DOI:10.3969/j.issn.1006-1959.2024.14.005
基于1D-ICNN的高维度数据下老年自评健康预测方法
Self-rated Health Prediction Method for the Elderly Based on 1D-ICNN High-dimensional Data
摘要
Abstract
The self-rated health of the elderly is an important factor to reflect the health status of the elderly,and it is of great significance to provide reference for improving the health level of the elderly.In order to understand the main factors affecting the self-rated health of the rural elderly in China and achieve accurate prediction,this study first explored the mechanism of different influencing factors on the self-rated health of the elderly based on the survey data of the elderly care demand in Yueyang County,Hunan Province in 2022.Then,based on the significant influencing factors,an improved one-dimensional convolutional neural network(1D-ICNN)based on cross entropy and variable learning rate is proposed to construct a self-rated health prediction model for the elderly in the case of high-dimensional data features,so as to solve the problems of inaccurate prediction and instability of 1D-CNN.This study shows that the self-rated health of the elderly is related to factors such as education level,political outlook,marital status,occupation and annual income.In the case of higher dimensional data features,the 1D-ICNN model has better prediction results.The application and popularization of this method can provide an empirical basis for accurately predicting the health status of the elderly and achieving"healthy aging".关键词
老年人/自评健康/一维卷积神经网络/预测模型Key words
Elderly/Self-rated health/One-dimensional convolutional neural network/Prediction model分类
信息技术与安全科学引用本文复制引用
李玥,张承蒙,黄成烨,索浩宇,胡新悦,刘娜,张雅璐,陈功..基于1D-ICNN的高维度数据下老年自评健康预测方法[J].医学信息,2024,37(14):25-32,8.基金项目
1.中国工程院战略研究与咨询项目(编号:2022-XBZD-30) （编号:2022-XBZD-30）
2.国家社会科学基金青年项目(编号:22CRK005) （编号:22CRK005）
