ArticleJournal of healthcare engineering2022
Hemodynamic Analysis of Pipeline Embolization Device Stent for Treatment of Giant Intracranial Aneurysm under Unsupervised Learning Algorithm.
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 It has been retracted, and should not be counted.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 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.
- Global trend in research of intracranial aneurysm management with artificial intelligence technology: a bibliometric analysis.Quantitative imaging in medicine and surgery · 2024Article
- Retracted: Hemodynamic Analysis of Pipeline Embolization Device Stent for Treatment of Giant Intracranial Aneurysm under Unsupervised Learning Algorithm.Journal of healthcare engineering · 2023Article
Corrections and comments
- Retraction · 2023-08-02Concerns/Issues about Data · 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/FB93166FFA6596AA7C7F57131F7EAD
- Retracted
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To treat large intracranial aneurysms, pipeline embolization device (PED) stent with unsupervised learning algorithms was utilized. Unsupervised learning model algorithm was used to screen aneurysm health big data, find aneurysm blood flow and PED stent positioning characteristic parameters, and guide PED stent treatment of intracranial aneurysms. The research objects were 100 patients with intracranial large aneurysm admitted to X Hospital of X Province from June 2020 to June 2021, who were enrolled into two groups. One group used the prototype transfer generative adversarial network (PTGAN) model to measure mean blood flow and mean vascular pressure and guide the placement of PED stents (PTGAN group). The other group did not use the model to place PED (control group). The PTGAN model can learn feature information from horizontal and vertical directions, with smooth edges and prominent features, which can effectively extract the main morphological and texture features of aneurysms. Compared with the convolutional neural network (CNN) model, the accuracy of the PTGAN model increased by 8.449% (87.452%-79.003%), and the precision increased by 8.347% (91.23%-82.883%). The recall rate increased by 7.011% (87.231%-80.22%), and the
Indexed as
Identifiers
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.