ArticleJournal of healthcare engineering2021
Application of the Artificial Neural Network in the Diagnosis of Infantile Bronchial Bridge with 64-Slice Multislice Spiral CT.
Article in Journal of healthcare engineering, 2021. 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 It has been retracted, and should not be counted.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 2 papers.
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
2 citing papers in PubMed, 2 citations in OpenAlex.
- Proposing new early detection indicators for pancreatic cancer: Combining machine learning and neural networks for serum miRNA-based diagnostic model.Frontiers in oncology · 2023Article
- Retracted: Application of the Artificial Neural Network in the Diagnosis of Infantile Bronchial Bridge with 64-Slice Multislice Spiral CT.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· Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Informed/Patient Consent - None/Withdrawn · Investigation by Journal/Publisher · Investigation by Third Party · Lack of IRB/IACUC Approval and/or Compliance · Paper Mill · Computer-Aided Content or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
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective is to study the application of spiral CT in the diagnosis of the trachea in children. In this study, the effect of 64-slice multislice spiral CT in diagnosing infant bronchial bridge was studied based on an artificial neural network. From June 2020 to December 2020, 100 cases of children with the trachea in the outpatient department of our hospital were selected as the research object. They were divided into the study group and the control group, with 50 cases in each group. The results showed that among the 50 cases in the control group, 42 cases were found to have a bronchial foreign body and 8 cases were missed; the detection rate was 84%. There were 7 cases of trachea foreign body, 15 cases of left bronchial foreign body, 14 cases of right bronchial foreign body, and 6 cases of medium bronchial foreign body. The detection rate of the study group was significantly higher than that of the control group, with a statistical significance (
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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.