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Construction of a Physical and Medical Care Integrated Model for the Elderly in the Community Based on Artificial Intelligence and Machine Learning

With the increasingly serious population aging, economic system transformation, and social transformation, the elderly have an increasingly strong demand for the elderly care service industry, but the development of China's elderly care service industry started late, and there are still many pr...

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Detalles Bibliográficos
Autores principales: Yang, Zongyou, Xia, Siyong, Feng, Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896920/
https://www.ncbi.nlm.nih.gov/pubmed/35251565
http://dx.doi.org/10.1155/2022/3678577
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author Yang, Zongyou
Xia, Siyong
Feng, Sheng
author_facet Yang, Zongyou
Xia, Siyong
Feng, Sheng
author_sort Yang, Zongyou
collection PubMed
description With the increasingly serious population aging, economic system transformation, and social transformation, the elderly have an increasingly strong demand for the elderly care service industry, but the development of China's elderly care service industry started late, and there are still many problems. For how to build a better elderly care service model, under the current situation of shortage of elderly care resources, community elderly care may become a solution. By analyzing the status quo, existing problems and development trends of home-based care services in Hangzhou's community, and learning from foreign experience, it explores the establishment of a “integrated physical, medical, and nursing care” community health management model for the elderly and provides a perfect solution for the development of Hangzhou's community elderly care services countermeasures and suggestions for mode operation. Based on the evaluation, problem analysis, and empirical research on the current situation of home care services in Hangzhou communities, this paper draws on relatively mature community care practices, proposes to build a community elderly health management model that combines medical care and care, and improves and innovates the overall design and medical care of the elderly service model measures for the health management of the elderly in the integrated community. The experimental results of this study show that, according to the demand for elderly care services, elderly people in need of care account for 86.6%, 79.5%, and 68.4% of the elderly population, especially in the areas of medical care, life care, and housekeeping services.
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spelling pubmed-88969202022-03-05 Construction of a Physical and Medical Care Integrated Model for the Elderly in the Community Based on Artificial Intelligence and Machine Learning Yang, Zongyou Xia, Siyong Feng, Sheng J Healthc Eng Research Article With the increasingly serious population aging, economic system transformation, and social transformation, the elderly have an increasingly strong demand for the elderly care service industry, but the development of China's elderly care service industry started late, and there are still many problems. For how to build a better elderly care service model, under the current situation of shortage of elderly care resources, community elderly care may become a solution. By analyzing the status quo, existing problems and development trends of home-based care services in Hangzhou's community, and learning from foreign experience, it explores the establishment of a “integrated physical, medical, and nursing care” community health management model for the elderly and provides a perfect solution for the development of Hangzhou's community elderly care services countermeasures and suggestions for mode operation. Based on the evaluation, problem analysis, and empirical research on the current situation of home care services in Hangzhou communities, this paper draws on relatively mature community care practices, proposes to build a community elderly health management model that combines medical care and care, and improves and innovates the overall design and medical care of the elderly service model measures for the health management of the elderly in the integrated community. The experimental results of this study show that, according to the demand for elderly care services, elderly people in need of care account for 86.6%, 79.5%, and 68.4% of the elderly population, especially in the areas of medical care, life care, and housekeeping services. Hindawi 2022-02-25 /pmc/articles/PMC8896920/ /pubmed/35251565 http://dx.doi.org/10.1155/2022/3678577 Text en Copyright © 2022 Zongyou Yang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yang, Zongyou
Xia, Siyong
Feng, Sheng
Construction of a Physical and Medical Care Integrated Model for the Elderly in the Community Based on Artificial Intelligence and Machine Learning
title Construction of a Physical and Medical Care Integrated Model for the Elderly in the Community Based on Artificial Intelligence and Machine Learning
title_full Construction of a Physical and Medical Care Integrated Model for the Elderly in the Community Based on Artificial Intelligence and Machine Learning
title_fullStr Construction of a Physical and Medical Care Integrated Model for the Elderly in the Community Based on Artificial Intelligence and Machine Learning
title_full_unstemmed Construction of a Physical and Medical Care Integrated Model for the Elderly in the Community Based on Artificial Intelligence and Machine Learning
title_short Construction of a Physical and Medical Care Integrated Model for the Elderly in the Community Based on Artificial Intelligence and Machine Learning
title_sort construction of a physical and medical care integrated model for the elderly in the community based on artificial intelligence and machine learning
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896920/
https://www.ncbi.nlm.nih.gov/pubmed/35251565
http://dx.doi.org/10.1155/2022/3678577
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