Intelligent Prediction and Optimization Algorithm for Chronic Disease Rehabilitation in Sports Using Big Data.

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  • Author(s): Zhang X;Zhang X; Wang X; Wang X
  • Source:
    Journal of healthcare engineering [J Healthc Eng] 2021 Apr 30; Vol. 2021, pp. 9920421. Date of Electronic Publication: 2021 Apr 30 (Print Publication: 2021).
  • Publication Type:
    Journal Article; Retracted Publication
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: Hindawi Publishing Country of Publication: England NLM ID: 101528166 Publication Model: eCollection Cited Medium: Internet ISSN: 2040-2309 (Electronic) Linking ISSN: 20402295 NLM ISO Abbreviation: J Healthc Eng Subsets: MEDLINE
    • Publication Information:
      Publication: 2016-2024 : London: Hindawi Publishing
      Original Publication: [Essex] : Multi-Science Pub.
    • Subject Terms:
      Big Data* ; Sports*; Aged ; Algorithms ; Chronic Disease ; Humans
    • Abstract:
      This paper investigates chronic diseases in the older population in the Chinese province of Henan and analyzes the rehabilitation needs and the current supply of related services in different levels of medical and elderly care institutions. We explore the fundamental causes for the diversified needs and insufficient supply of chronic disease patients in professional medical services and daily care. Using big data and deep learning (DL) in the sports domain, we propose a novel and intelligent prediction system for chronic diseases. Our model explores effective sinking methods of high-quality medical resources, training and guidance practices, assistance and guidance measures, and the ability to improve the grassroots services so that more chronically ill populations can stay in the community family as long as possible. In such an environment, they can receive cheap, safe, and suitable services. It can also lead to further improvement in constructing the government's regional medical rehabilitation care service system and can formulate long-term care relevant compensation policies.
      Competing Interests: The authors declare that they have no conflicts of interest.
      (Copyright © 2021 Xuelei Zhang and Xiaofeng Wang.)
    • Comments:
      Retraction in: J Healthc Eng. 2023 Oct 11;2023:9789012. (PMID: 37860325)
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    • Publication Date:
      Date Created: 20210519 Date Completed: 20220418 Latest Revision: 20231020
    • Publication Date:
      20231020
    • Accession Number:
      PMC8110381
    • Accession Number:
      10.1155/2021/9920421
    • Accession Number:
      34007431