ReviewJournal of personalized medicine2021
Application of Artificial Intelligence in COVID-19 Diagnosis and Therapeutics.
Review in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses 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
16 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Opportunities and challenges of artificial intelligence in public health: a systematic review on technological efficacy, ethical dilemmas, and governance pathways.Frontiers in public health · 2025Pooled it
- Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review.Journal of medical systems · 2024Pooled it
- Diagnostic Test Accuracy of Deep Learning Prediction Models on COVID-19 Severity: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2023Pooled it
- Infectious Disease Surveillance in the Era of Big Data and AI: Opportunities and Pitfalls.Cureus · 2025Review
- Confidence-Aware Severity Assessment of Lung Disease from Chest X-Rays Using Deep Neural Network on a Multi-Reader Dataset.Journal of imaging informatics in medicine · 2025Article
- The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.Molecular biomedicine · 2025Review
- Learning lessons from the COVID-19 pandemic for real-world evidence research in oncology-shared perspectives from international consortia.ESMO open · 2023Article
- Analysis of super-enhancer using machine learning and its application to medical biology.Briefings in bioinformatics · 2023Review
- Ensemble deep honey architecture for COVID-19 prediction using CT scan and chest X-ray images.Multimedia systems · 2023Article
- Learning from real world data about combinatorial treatment selection for COVID-19.Frontiers in artificial intelligence · 2023Article
- Introducing AI to the molecular tumor board: one direction toward the establishment of precision medicine using large-scale cancer clinical and biological information.Experimental hematology & oncology · 2022Review
- Application of non-negative matrix factorization in oncology: one approach for establishing precision medicine.Briefings in bioinformatics · 2022Review
- Automated Endocardial Border Detection and Left Ventricular Functional Assessment in Echocardiography Using Deep Learning.Biomedicines · 2022Article
- Determination of the Severity and Percentage of COVID-19 Infection through a Hierarchical Deep Learning System.Journal of personalized medicine · 2022Article
- Review
- Single-Cell Analysis Using Machine Learning Techniques and Its Application to Medical Research.Biomedicines · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
The coronavirus disease 2019 (COVID-19) pandemic began at the end of December 2019, giving rise to a high rate of infections and causing COVID-19-associated deaths worldwide. It was first reported in Wuhan, China, and since then, not only global leaders, organizations, and pharmaceutical/biotech companies, but also researchers, have directed their efforts toward overcoming this threat. The use of artificial intelligence (AI) has recently surged internationally and has been applied to diverse aspects of many problems. The benefits of using AI are now widely accepted, and many studies have shown great success in medical research on tasks, such as the classification, detection, and prediction of disease, or even patient outcome. In fact, AI technology has been actively employed in various ways in COVID-19 research, and several clinical applications of AI-equipped medical devices for the diagnosis of COVID-19 have already been reported. Hence, in this review, we summarize the latest studies that focus on medical imaging analysis, drug discovery, and therapeutics such as vaccine development and public health decision-making using AI. This survey clarifies the advantages of using AI in the fight against COVID-19 and provides future directions for tackling the COVID-19 pandemic using AI techniques.
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.