ArticleJournal of environmental and public health2022
Application Model of Public Health Visual Art Creation Concept Based on Artificial Intelligence Technology in Venice Biennale.
Article in Journal of environmental and public health, 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 It has been retracted, and should not be counted.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, 1 citations in OpenAlex.
- Retracted: Application Model of Public Health Visual Art Creation Concept Based on Artificial Intelligence Technology in Venice Biennale.Journal of environmental and public health · 2023Article
Corrections and comments
- Retraction · 2023-06-28Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/3D43A271AE3F640847D9396B4BFAE6
- Retracted
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There are some problems in the creation process of public health visual art works, such as low accuracy and poor content quality. In order to further improve the accuracy and quality of artistic creation, based on artificial intelligence technology, a neural network model and an error backpropagation algorithm are used to analyze artistic creation, so as to obtain the corresponding optimization model. This model can analyze the application of public health visual art creation concepts in the Venice Biennale, so as to obtain the corresponding model calculation results under different indicators. Finally, data comparison is used to verify the accuracy of the model. Relevant studies show that activation values have different trends in connection weights under the action of different factors. The fluctuation of the curve is obvious in the initial state, but when the factor is high, the corresponding connection weight tends to be stable gradually. The range of learning rate in the initial state is relatively small, and the connection weights show a V-shaped change at higher factors. It can be seen from the curve corresponding to the
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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.