ArticleJournal of healthcare engineering2022
Effects of Aerobic Training on Cardiopulmonary Function Based on Multiple Linear Regression Analysis.
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 It has been retracted, and should not be counted.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: Effects of Aerobic Training on Cardiopulmonary Function Based on Multiple Linear Regression Analysis.Journal of healthcare engineering · 2023Article
Corrections and comments
- Retraction · 2023-07-12Concerns/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· Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Informed/Patient Consent - None/Withdrawn · Investigation by Journal/Publisher · Investigation by Third Party · Lack of IRB/IACUC Approval and/or Compliance · Paper Mill · Computer-Aided Content or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
In order to study the effect of aerobic training exercise on cardiopulmonary function of the human body, in this study, multiple linear regression based on the particle swarm optimization cardiopulmonary function test method of constructing the sports cardiopulmonary function test model is used. The traditional multiple linear regression after 41 iteration achieves convergence, and after the particle swarm optimization, about 25 times, convergence is achieved. Moreover, the convergence error of pSO is less than that of traditional multiple linear regression algorithm, which verifies the effectiveness of PSO. This method can effectively detect cardiopulmonary function of athletes before and after aerobic training, and the modeling accuracy is high, and the detection performance of cardiopulmonary function of aerobic training is better than the traditional relational model algorithm, which provides a new way for cardiopulmonary model detection of the human body.
Indexed as
Identifiers
What Socratic 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 Socratic graph.