ArticleIEEE access : practical innovations, open solutions2020
COVID-19 Control by Computer Vision Approaches: A Survey.
Article in IEEE access : practical innovations, open solutions, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.
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.
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
49 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Comprehensive Review of Artificial Intelligence in Prevention and Treatment of COVID-19 Pandemic.Frontiers in genetics · 2022Pooled it
- Clinician and Visitor Activity Patterns in an Intensive Care Unit Room: A Study to Examine How Ambient Monitoring Can Inform the Measurement of Delirium Severity and Escalation of Care.Journal of imaging · 2024Article
- Remote intelligent perception system for multi-object detection.Frontiers in neurorobotics · 2024Article
- A survey on computer vision based human analysis in the COVID-19 era.Image and vision computing · 2023Article
- Uncertain-CAM: Uncertainty-Based Ensemble Machine Voting for Improved COVID-19 CXR Classification and Explainability.Diagnostics (Basel, Switzerland) · 2023Article
- A comprehensive review on variants of SARS-CoVs-2: Challenges, solutions and open issues.Computer communications · 2023Article
- Human behavior in the time of COVID-19: Learning from big data.Frontiers in big data · 2023Review
- Article
- Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain.Diagnostics (Basel, Switzerland) · 2022Article
- SUFEMO: A superpixel based fuzzy image segmentation method for COVID-19 radiological image elucidation.Applied soft computing · 2022Article
- AI for COVID-19 Detection from Radiographs: Incisive Analysis of State of the Art Techniques, Key Challenges and Future Directions.Ingenierie et recherche biomedicale : IRBM = Biomedical engineering and research · 2022Review
- Artificial Intelligence and COVID-19: A Systematic umbrella review and roads ahead.Journal of King Saud University. Computer and information sciences · 2022Review
- An Unsupervised Fuzzy Clustering Approach for Early Screening of COVID-19 From Radiological Images.IEEE transactions on fuzzy systems : a publication of the IEEE Neural Networks Council · 2022Article
- Topology optimization search of deep convolution neural networks for CT and X-ray image classification.BMC medical imaging · 2022Article
- Generalizability assessment of COVID-19 3D CT data for deep learning-based disease detection.Computers in biology and medicine · 2022Article
- Current Artificial Intelligence (AI) Techniques, Challenges, and Approaches in Controlling and Fighting COVID-19: A Review.International journal of environmental research and public health · 2022Review
- Artificial Intelligence for COVID-19 Detection in Medical Imaging-Diagnostic Measures and Wasting-A Systematic Umbrella Review.Journal of clinical medicine · 2022Review
- WMR-DepthwiseNet: A Wavelet Multi-Resolution Depthwise Separable Convolutional Neural Network for COVID-19 Diagnosis.Diagnostics (Basel, Switzerland) · 2022Article
- COVID-19 Diagnosis from Chest X-ray Images Using a Robust Multi-Resolution Analysis Siamese Neural Network with Super-Resolution Convolutional Neural Network.Diagnostics (Basel, Switzerland) · 2022Article
- Virtual Reality visualization for computerized COVID-19 lesion segmentation and interpretation.Biomedical signal processing and control · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic has triggered an urgent call to contribute to the fight against an immense threat to the human population. Computer Vision, as a subfield of artificial intelligence, has enjoyed recent success in solving various complex problems in health care and has the potential to contribute to the fight of controlling COVID-19. In response to this call, computer vision researchers are putting their knowledge base at test to devise effective ways to counter COVID-19 challenge and serve the global community. New contributions are being shared with every passing day. It motivated us to review the recent work, collect information about available research resources, and an indication of future research directions. We want to make it possible for computer vision researchers to find existing and future research directions. This survey article presents a preliminary review of the literature on research community efforts against COVID-19 pandemic.
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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.