ReviewBioMed research international2021
Research Progress of Deep Learning in the Diagnosis and Prevention of Stroke.
Review in BioMed research international, 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 It has been retracted, and should not be counted.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 5 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
5 citing papers in PubMed, 23 citations in OpenAlex.
- From data to decisions: AI and functional connectivity for diagnosis, prognosis, and recovery prediction in stroke.GeroScience · 2025Article
- Evaluating deep learning techniques for identifying tongue features in subthreshold depression: a prospective observational study.Frontiers in psychiatry · 2024Article
- CNN-Res: deep learning framework for segmentation of acute ischemic stroke lesions on multimodal MRI images.BMC medical informatics and decision making · 2023Article
- Using Neural Networks Algorithm in Ischemic Stroke Diagnosis: A Systematic Review.Journal of multidisciplinary healthcare · 2023Review
- Research on prognostic risk assessment model for acute ischemic stroke based on imaging and multidimensional data.Frontiers in neurology · 2023Article
Corrections and comments
- Retraction · 2024-01-09Concerns/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
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In order to evaluate the importance of deep learning techniques in stroke diseases, this paper systematically reviews the relevant literature. Deep learning techniques have a significant impact on the diagnosis, treatment, and prediction of stroke. In addition, this study also discusses the current bottlenecks and the future development prospects of deep learning technology.
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.