ReviewInternational journal of environmental research and public health2021
Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions.
Review in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 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
50 citing papers in PubMed, 3 syntheses or guidelines 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
- The COVID-19 epidemic analysis and diagnosis using deep learning: A systematic literature review and future directions.Computers in biology and medicine · 2022Pooled it
- The Use and Performance of Artificial Intelligence in Prosthodontics: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- AI-Driven Approaches for the Detection, Classification, and Surveillance of Viral Pathogens: Current Advances, Challenges, and Future Directions.Pathogens (Basel, Switzerland) · 2026Review
- A Dirichlet Distribution-Based Complex Ensemble Approach for Breast Cancer Classification from Ultrasound Images with Transfer Learning and Multiphase Spaced Repetition Method.Journal of imaging informatics in medicine · 2026Article
- Machine Learning-Powered Smart Healthcare Systems in the Era of Big Data: Applications, Diagnostic Insights, Challenges, and Ethical Implications.Diagnostics (Basel, Switzerland) · 2025Review
- Machine learning in solid organ transplantation: Charting the evolving landscape.World journal of transplantation · 2025Article
- H-DSAE: a hybrid technique to recognize heart disease.Frontiers in physiology · 2025Article
- Cough2COVID-19 detection using an enhanced multi layer ensemble deep learning framework and CoughFeatureRanker.Scientific reports · 2024Article
- Applying Machine Learning Techniques to Implementation Science.Online journal of public health informatics · 2024Article
- Application of artificial intelligence (AI) to control COVID-19 pandemic: Current status and future prospects.Heliyon · 2024Review
- RApid Throughput Screening for Asymptomatic COVID-19 Infection With an Electrocardiogram: A Prospective Observational Study.Mayo Clinic proceedings. Digital health · 2023Article
- A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media.Sensors (Basel, Switzerland) · 2023Review
- A deep learning predictive model for public health concerns and hesitancy toward the COVID-19 vaccines.Scientific reports · 2023Article
- A survey of machine learning-based methods for COVID-19 medical image analysis.Medical & biological engineering & computing · 2023Review
- A Survey of COVID-19 Diagnosis Using Routine Blood Tests with the Aid of Artificial Intelligence Techniques.Diagnostics (Basel, Switzerland) · 2023Review
- Emerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectives.Biomedical signal processing and control · 2023Review
- Clinical Hematochemical Parameters in Differential Diagnosis between Pediatric SARS-CoV-2 and Influenza Virus Infection: An Automated Machine Learning Approach.Children (Basel, Switzerland) · 2023Article
- Superior possibilities and upcoming horizons for nanoscience in COVID-19: noteworthy approach for effective diagnostics and management of SARS-CoV-2 outbreak.Chemicke zvesti · 2023Review
- Equilibrium-based COVID-19 diagnosis from routine blood tests: A sparse deep convolutional model.Expert systems with applications · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have also been instrumental in tackling the outbreak of Coronavirus (COVID-19), which has been happening around the world. The SARS-CoV-2 virus-induced COVID-19 epidemic has spread rapidly across the world, leading to international outbreaks. The COVID-19 fight to curb the spread of the disease involves most states, companies, and scientific research institutions. In this research, we look at the Artificial Intelligence (AI)-based ML and DL methods for COVID-19 diagnosis and treatment. Furthermore, in the battle against COVID-19, we summarize the AI-based ML and DL methods and the available datasets, tools, and performance. This survey offers a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how ML and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of COVID-19. Details of challenges and future directions are also provided.
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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.