ReviewComputers in biology and medicine2021
Medical imaging and computational image analysis in COVID-19 diagnosis: A review.
Review in Computers in biology and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
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.
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Who cites it
13 citing papers in PubMed, 43 citations in OpenAlex.
- Deep Learning Network Selection and Optimized Information Fusion for Enhanced COVID-19 Detection: A Literature Review.Diagnostics (Basel, Switzerland) · 2025Review
- COVID-19 health data prediction: a critical evaluation of CNN-based approaches.Scientific reports · 2025Article
- Anesthetic Management Recommendations Using a Machine Learning Algorithm to Reduce the Risk of Acute Kidney Injury After Cardiac Surgeries.Anesthesiology and pain medicine · 2024Article
- Advanced slime mould algorithm incorporating differential evolution and Powell mechanism for engineering design.iScience · 2023Article
- Improved Colony Predation Algorithm Optimized Convolutional Neural Networks for Electrocardiogram Signal Classification.Biomimetics (Basel, Switzerland) · 2023Article
- Collaborative training of medical artificial intelligence models with non-uniform labels.Scientific reports · 2023Article
- An enhanced decision-making framework for predicting future trends of sharing economy.PloS one · 2023Article
- Application of Machine Learning and Deep Learning Techniques for COVID-19 Screening Using Radiological Imaging: A Comprehensive Review.SN computer science · 2023Article
- COVID-19 therapy optimization by AI-driven biomechanical simulations.European physical journal plus · 2023Article
- COVID-19 infection prediction from CT scan images of lungs using Iterative Convolution Neural Network model.Advances in engineering software (Barking, London, England : 1992) · 2022Article
- Ultrafast PCR Detection of COVID-19 by Using a Microfluidic Chip-Based System.Bioengineering (Basel, Switzerland) · 2022Article
- Impact of computational approaches in the fight against COVID-19: an AI guided review of 17 000 studies.Briefings in bioinformatics · 2022Review
- Novel Crow Swarm Optimization Algorithm and Selection Approach for Optimal Deep Learning COVID-19 Diagnostic Model.Computational intelligence and neuroscience · 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
7 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. The disease presents with symptoms such as shortness of breath, fever, dry cough, and chronic fatigue, amongst others. The disease may be asymptomatic in some patients in the early stages, which can lead to increased transmission of the disease to others. This study attempts to review papers on the role of imaging and medical image computing in COVID-19 diagnosis. For this purpose, PubMed, Scopus and Google Scholar were searched to find related studies until the middle of 2021. The contribution of this study is four-fold: 1) to use as a tutorial of the field for both clinicians and technologists, 2) to comprehensively review the characteristics of COVID-19 as presented in medical images, 3) to examine automated artificial intelligence-based approaches for COVID-19 diagnosis, 4) to express the research limitations in this field and the methods used to overcome them. Using machine learning-based methods can diagnose the disease with high accuracy from medical images and reduce time, cost and error of diagnostic procedure. It is recommended to collect bulk imaging data from patients in the shortest possible time to improve the performance of COVID-19 automated diagnostic methods.
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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.