ArticleClinical and translational medicine2020
COVID-19 diagnostic testing: Technology perspective.
Article in Clinical and translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 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
49 citing papers in PubMed, 89 citations in OpenAlex.
- Evaluation of the safety and efficacy of using human menstrual blood-derived mesenchymal stromal cells in treating severe and critically ill COVID-19 patients: An exploratory clinical trial.Clinical and translational medicine · 2021Trial
- Application of Generative Adversarial Networks to Improve COVID-19 Classification on Ultrasound Images.Journal of imaging · 2025Article
- Evaluating the impact of COVID-19 on cancer care: a comprehensive analysis of treatment modifications, risk factors, and patient outcomes.BMC infectious diseases · 2025Article
- Advances in Virus Biorecognition and Detection Techniques for the Surveillance and Prevention of Infectious Diseases.Biosensors · 2025Review
- Public perception of medical detection dogs and other COVID-19 testing strategies.Frontiers in public health · 2025Article
- Portable wide-field femtoliter-chamber imaging system for point-of-care digital bioanalysis.iScience · 2024Article
- A tree-based explainable AI model for early detection of Covid-19 using physiological data.BMC medical informatics and decision making · 2024Article
- From Detection to Protection: Antibodies and Their Crucial Role in Diagnosing and Combatting SARS-CoV-2.Vaccines · 2024Review
- Recent Advances in Lateral Flow Assays for Viral Protein Detection with Nanomaterial-Based Optical Sensors.Biosensors · 2024Review
- A Systematic Review and Meta-Analysis Comparing the Diagnostic Accuracy Tests of COVID-19.Diagnostics (Basel, Switzerland) · 2023Review
- Stopping epidemics when and where they occur.Lancet (London, England) · 2023Article
- Graph data science and machine learning for the detection of COVID-19 infection from symptoms.PeerJ. Computer science · 2023Article
- Effectiveness of RCTs Pooling Evidence on Mesenchymal Stem Cell (MSC) Therapeutic Applications During COVID-19 Epidemic: A Systematic Review.Biologics : targets & therapy · 2023Review
- Screening and confirmation tests for SARS-CoV-2: benefits and drawbacks.Beni-Suef University journal of basic and applied sciences · 2023Review
- Screening of COVID-19 Based on GLCM Features from CT Images Using Machine Learning Classifiers.SN computer science · 2023Article
- Development of a Single-Chain Variable Fragment of CR3022 for a Plasmonic-Based Biosensor Targeting the SARS-CoV-2 Spike Protein.Biosensors · 2022Article
- Effectiveness of SARS-CoV-2 Vaccines for Short- and Long-Term Immunity: A General Overview for the Pandemic Contrast.International journal of molecular sciences · 2022Review
- Smartphone-based sensitive detection of SARS-CoV-2 from saline gargle samples via flow profile analysis on a paper microfluidic chip.Biosensors & bioelectronics · 2022Article
- Effectiveness evaluation of different feature extraction methods for classification of covid-19 from computed tomography images: A high accuracy classification study.Biomedical signal processing and control · 2022Article
- Molecular and antigen tests, and sample types for diagnosis of COVID-19: a review.Future virology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
The corona virus disease 2019 (COVID-19) is a highly contagious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). More than 18 million people were infected with a total of 0.7 million deaths in ∼188 countries. Controlling the spread of SARS-CoV-2 is therefore inherently dependent on identifying and isolating infected individuals, especially since COVID-19 can result in little to no symptoms. Here, we provide a comprehensive review of the different primary technologies used to test for COVID-19 infection, discuss the advantages and disadvantages of each technology, and highlight the studies that have employed them. We also describe technologies that have the potential to accelerate SARS-CoV-2 detection in the future, including digital PCR, CRISPR, and microarray. Finally, remaining challenges in COVID-19 diagnostic testing are discussed, including (a) the lack of universal standards for diagnostic testing; (b) the identification of appropriate sample collection site(s); (c) the difficulty in performing large population screening; and (d) the limited understanding of SARS-COV-2 viral invasion, replication, and transmission.
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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.