ArticleJournal of healthcare engineering2022
Analysis of the Model for Sports Enhancing Human Health Using Data Mining.
Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Retracted: Analysis of the Model for Sports Enhancing Human Health Using Data Mining.Journal of healthcare engineering · 2023Article
Corrections and comments
- Retraction · 2023-10-11Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Informed/Patient Consent - None/Withdrawn · Investigation by Journal/Publisher · Investigation by Third Party · Lack of IRB/IACUC Approval and/or Compliance · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The problems of low reliability and the high fitting degree of mutual information feature extraction of traditional sports to human health enhancement model are analyzed. We analyze and study the sports to human health enhancement model using data mining. The model consists of a data layer, a logic layer, and a presentation layer. Sports project data, real-time sports data, and health monitoring data are collected in the data layer, and the collected data are transmitted to the logic layer. The logical layer uses the dynamic difference feature classification algorithm of data mining to fuse human health data, extract the mutual information features of human health, and input the features into the long short-term memory (LSTM) neural network, which outputs the pattern recognition results of sports health after forward and reverse operations. The results of sports health pattern recognition are input into the display layer, and the enhancing effect of sports on human health is presented for users by constructing a model of sports on human health. The results show that the effect of sports on human health enhancement analyzed by the model in this paper is extremely accurate, which can significantly improve the health level of community residents and college students. When the number of data is about 600, it remains at about 0.05, indicating that this model has high reliability, and the fitting degree of mutual information feature extraction is up to 99.82%. It has certain practical application value.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.