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Tytuł:
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Long-Term Assessment of Rehabilitation Treatment of Sports through Artificial Intelligence Research.
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Autorzy:
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Zeng C; Guangzhou Institute of Technology, Guangzhou, Guangdong 510075, China.
Huang Y; Guangdong Foreign Trade School, Guangzhou, Guangdong 510520, China.
Yu L; Guangzhou Institute of Technology, Guangzhou, Guangdong 510075, China.
Zeng Q; Rehabilitation Department, The Fifth Affiliated Hospital, Southern Medical University, Guangzhou 510900, China.
Wang B; Rehabilitation Department, The Fifth Affiliated Hospital, Southern Medical University, Guangzhou 510900, China.
Xu Y; Guangdong Eco-Engineering Polytechnic, Guangzhou, Guangdong 510520, China.
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Źródło:
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Computational and mathematical methods in medicine [Comput Math Methods Med] 2021 Dec 22; Vol. 2021, pp. 4980718. Date of Electronic Publication: 2021 Dec 22 (Print Publication: 2021).
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Typ publikacji:
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Journal Article; Randomized Controlled Trial
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Język:
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English
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Imprint Name(s):
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Publication: 2011- : New York : Hindawi
Original Publication: London : Taylor & Francis, c2006-
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MeSH Terms:
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Artificial Intelligence*
Sports*
Athletic Injuries/*rehabilitation
Aged ; China ; Computational Biology ; Diabetes Mellitus/physiopathology ; Diabetes Mellitus/therapy ; Female ; Humans ; Machine Learning ; Male ; Middle Aged ; Precision Medicine/methods ; Precision Medicine/statistics & numerical data ; Sports Medicine/methods ; Sports Medicine/organization & administration ; Sports Medicine/statistics & numerical data
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References:
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Endocrinol Metab Clin North Am. 1997 Sep;26(3):443-74. (PMID: 9314008)
Diabetologia. 2011 Apr;54(4):762-6. (PMID: 21212932)
Can J Diabetes. 2016 Feb;40(1):95-104. (PMID: 26455762)
Healthc Inform. 1990 Mar;7(3):54. (PMID: 10120641)
J Diabetes Investig. 2015 May;6(3):289-94. (PMID: 25969713)
J Korean Acad Nurs. 2013 Apr;43(2):203-14. (PMID: 23703598)
J Gerontol B Psychol Sci Soc Sci. 2006 Mar;61(2):S62-70. (PMID: 16497962)
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Entry Date(s):
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Date Created: 20220103 Date Completed: 20220211 Latest Revision: 20220429
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Update Code:
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20240104
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PubMed Central ID:
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PMC8716213
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DOI:
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10.1155/2021/4980718
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PMID:
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34976108
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Background: Artificial intelligence (AI) technology has been incorporated into all walks of life, especially the integration of machine learning and health management has achieved very significant progress and results. It is very necessary to analyze personalized sports health management services and long-term assessment of health issues in the era of AI.
Methods: This paper explores AI + personalized sports management service system design ideas, system operation process, management stage design, taking common chronic diseases, and diabetes as examples. 150 patients were divided into an observation group and a control group, and the blood glucose, blood pressure, blood lipid, and knowledge awareness rate were compared.
Results: The blood glucose, blood pressure, and blood lipid levels of the observation group all reduced, and the awareness rate of diabetes knowledge increased, which proved that the AI research has great value in sports rehabilitation research coupled with long term health assessment and is worth further research.
Conclusion: The AI research proposed in this paper is of far-reaching practical significance in helping the transformation and upgrading of the sports health management service industry, promoting the innovative development of sports health management service supply, and promoting national fitness and national health.
Competing Interests: The authors declare that there are no conflicts of interest.
(Copyright © 2021 Chaofan Zeng et al.)
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