Trial reportComputational and mathematical methods in medicine2022
Three-Dimensional Ultrasound Images in the Assessment of Bladder Tumor Health Monitoring under Deep Learning Algorithms.
Trial report 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 It has been retracted, and should not be counted.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 3 papers, 1 of them a synthesis that pooled it.
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
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Effects of Nursing Care for the Treatment of Patients with Bladder Cancer: A Systematic Review and Meta-analysis.Computational and mathematical methods in medicine · 2022Pooled it
- Bladder Cancer and Artificial Intelligence: Emerging Applications.The Urologic clinics of North America · 2024Review
- Retracted: Three-Dimensional Ultrasound Images in the Assessment of Bladder Tumor Health Monitoring under Deep Learning Algorithms.Computational and mathematical methods in medicine · 2023Article
Corrections and comments
- Retraction · 2023-12-13Compromised Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study was aimed at exploring the application value of three-dimensional (3D) ultrasound based on deep learning and continued nursing health monitoring (CNHM) mode in promoting the recovery of bladder cancer patients after surgery. 60 patients who underwent muscular noninvasive superficial bladder cancer and bladder perfusion treatment were selected as the research objects. The patients were randomly divided into two groups: an experimental group (30 cases) and a control group (30 cases). Patients in the experimental group adopted a CNHM model during the bladder perfusion treatment. The patients in control group adopted ordinary health monitoring mode. All patients underwent 3D ultrasound examination, and all images were processed using the convolutional neural network (CNN) algorithm. All patients were followed up regularly within 12 after the treatment. The imaging data, quality of life, satisfaction, and complications of the two groups of patients were compared in each time period. The ultrasound image processed by the CNN algorithm was clearer than that processed by the original method, showing higher image quality and more prominent lesion features. After 12 months of health monitoring intervention, the overall health status, scores of various functional areas, and score of functional subscales of the experimental group were greatly higher than those of the control group, and the differences were statistically significant (
Indexed as
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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.