ArticleComplex & intelligent systems2021
A systematic review on AI/ML approaches against COVID-19 outbreak.
Article in Complex & intelligent systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A composite ranking of risk factors for COVID-19 time-to-event data from a Turkish cohort.Computational biology and chemistry · 2022Pooled it
- Survey on mathematical modeling of infectious disease dynamics: insights and applications.BMC infectious diseases · 2026Review
- An overview of reviews on digital health interventions during COVID- 19 era: insights and lessons for future pandemics.Archives of public health = Archives belges de sante publique · 2025Article
- Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions.BMC medicine · 2024Review
- AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods.Osong public health and research perspectives · 2024Article
- Modern technologies and solutions to enhance surveillance and response systems for emerging zoonotic diseases.Science in One Health · 2024Review
- Harnessing Machine Learning in Early COVID-19 Detection and Prognosis: A Comprehensive Systematic Review.Cureus · 2023Review
- Combating Covid-19 using machine learning and deep learning: Applications, challenges, and future perspectives.Array (New York, N.Y.) · 2023Review
- Cardiovascular and Renal Comorbidities Included into Neural Networks Predict the Outcome in COVID-19 Patients Admitted to an Intensive Care Unit: Three-Center, Cross-Validation, Age- and Sex-Matched Study.Journal of cardiovascular development and disease · 2023Article
- Predicting the distribution of COVID-19 through CGAN-Taking Macau as an example.Frontiers in big data · 2023Article
- Influence of augmentation on the performance of the double ResNet-based model for chest X-ray classification.Polish journal of radiology · 2023Article
- Harnessing the power of AI: Advanced deep learning models optimization for accurate SARS-CoV-2 forecasting.PloS one · 2023Article
- Unsupervised natural language processing in the identification of patients with suspected COVID-19 infection.Cadernos de saude publica · 2023Observational
- A swarm-optimizer-assisted simulation and prediction model for emerging infectious diseases based on SEIR.Complex & intelligent systems · 2023Article
- Assessment of regional economic restorability under the stress of COVID-19 using the new interval type-2 fuzzy ORESTE method.Complex & intelligent systems · 2022Article
- A comparison of conventional and advanced electroanalytical methods to detect SARS-CoV-2 virus: A concise review.Chemosphere · 2022Review
- Forecasting daily Covid-19 cases in the world with a hybrid ARIMA and neural network model.Applied soft computing · 2022Article
- Who was at risk for COVID-19 late in the US pandemic? Insights from a population health machine learning model.Medical & biological engineering & computing · 2022Article
- Modeling approaches for early warning and monitoring of pandemic situations as well as decision support.Frontiers in public health · 2022Review
- Agent-based modeling and life cycle dynamics of COVID-19-related online collective actions.Complex & intelligent systems · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A pandemic disease, COVID-19, has caused trouble worldwide by infecting millions of people. The studies that apply artificial intelligence (AI) and machine learning (ML) methods for various purposes against the COVID-19 outbreak have increased because of their significant advantages. Although AI/ML applications provide satisfactory solutions to COVID-19 disease, these solutions can have a wide diversity. This increase in the number of AI/ML studies and diversity in solutions can confuse deciding which AI/ML technique is suitable for which COVID-19 purposes. Because there is no comprehensive review study, this study systematically analyzes and summarizes related studies. A research methodology has been proposed to conduct the systematic literature review for framing the research questions, searching criteria and relevant data extraction. Finally, 264 studies were taken into account after following inclusion and exclusion criteria. This research can be regarded as a key element for epidemic and transmission prediction, diagnosis and detection, and drug/vaccine development. Six research questions are explored with 50 AI/ML approaches in COVID-19, 8 AI/ML methods for patient outcome prediction, 14 AI/ML techniques in disease predictions, along with five AI/ML methods for risk assessment of COVID-19. It also covers AI/ML method in drug development, vaccines for COVID-19, models in COVID-19, datasets and their usage and dataset applications with AI/ML.
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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.