System Construction of Athlete Health Information Protection Based on Machine Learning Algorithm.
The exercise volume and exercise level can be quantitatively assessed by measuring and collecting athletes' health and exercise data. The protection of athletes' health information has lately become an important research topic due to a rise in sports activities. However, due to the nature of the dat...
| Published in: | BioMed Research International pp. 1 - 13 |
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| Main Authors: | , |
| Format: | equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
9/28/2022
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159378197&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159378197 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 9/28/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 159378197 159378197 159378197 10.1155/2022/5989819 159378197 ppf: 1 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: System Construction of Athlete Health Information Protection Based on Machine Learning Algorithm. aug: au: Liu, Long Fan, Xiaodong affil: Chongqing Preschool Education College, Wanzhou, 404100 Chongqing, China sug: subj: Athletes Health Information Management Machine Learning Algorithms Blockchain Sports Medicine Human Physical Fitness Access to Information Information Storage Privacy and Confidentiality Simulations Descriptive Statistics Data Security ab: The exercise volume and exercise level can be quantitatively assessed by measuring and collecting athletes' health and exercise data. The protection of athletes' health information has lately become an important research topic due to a rise in sports activities. However, due to the nature of the data and the limits of protection models, protecting athlete health data is a complex undertaking. Machine learning and blockchain have caused worldwide technological innovation, and it is bound to bring deep modifications to the sports industry. The main purpose of blockchain is security, decentralization, traceability, and credibility of the athlete's health data protection and gathering system. To progress and increase the sports industry and methodically assess the physical fitness of sportspersons' health information, this study concentrates on the Machine Learning and Blockchain-based Athlete Health Information Protection System (MLB-AHIPS) proposed in the sports industry. The ML technique is utilized to clean and handle the information to comprehend the recognition and secure managing of the sportsperson's fitness information. The system uses attribute-based access control, which permits dynamic and fine-grained access to athlete health data, and then stores the health data in the blockchain, which can be secured and tamper-proof by expressing the respective smart contracts. The simulation outcomes illustrate that the suggested MLB-AHIPS attains a high accuracy ratio of 97.8%, security ratio of 98.3%, an efficiency ratio of 97.1%, scalability ratio of 98.9%, and data access rate of 97.2% compared to other existing approach. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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