ArticleComputational and mathematical methods in medicine2022
Computed Tomography Image Features under Deep Learning Algorithm Applied in Staging Diagnosis of Bladder Cancer and Detection on Ceramide Glycosylation.
Article in Computational and mathematical methods in medicine, 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 It has been retracted, and should not be counted.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 5 papers.
What it found
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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.
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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.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Urological diagnostics based on kidney stone detection in CT imaging using YOLOv8 deep learning framework.Frontiers in medicine · 2026Article
- The genetic associations of lipidome on bladder cancer: a Mendelian randomization study.Discover oncology · 2025Article
- Glycosphingolipids as emerging attack points in bladder cancer.Discover oncology · 2025Review
- Artificial Intelligence in the Advanced Diagnosis of Bladder Cancer-Comprehensive Literature Review and Future Advancement.Diagnostics (Basel, Switzerland) · 2023Review
- Retracted: Computed Tomography Image Features under Deep Learning Algorithm Applied in Staging Diagnosis of Bladder Cancer and Detection on Ceramide Glycosylation.Computational and mathematical methods in medicine · 2023Article
Corrections and comments
- Retraction · 2023-11-01Concerns/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 · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The research is aimed at investigating computed tomography (CT) image based on deep learning algorithm and the application value of ceramide glycosylation in diagnosing bladder cancer. The images of ordinary CT detection were improved. In this study, 60 bladder cancer patients were selected and performed with ordinary CT detection, and the detection results were processed by CT based on deep learning algorithms and compared with pathological diagnosis. In addition, Western Blot technology was used to detect the expression of glucose ceramide synthase (GCS) in the cell membrane of tumor tissues and normal tissues of bladder. The comparison results found that, in simple CT clinical staging, the coincidence rates of T1 stage, T2a stage, T2b stage, T3 stage, and T4 stage were 28.56%, 62.51%, 78.94%, 84.61%, and 74.99%, respectively; and the total coincidence rate of CT clinical staging was 63.32%, which was greatly different from the clinical staging of pathological diagnosis (
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Registered trials
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