ArticlePeerJ. Computer science2021
Overview of current state of research on the application of artificial intelligence techniques for COVID-19.
Article in PeerJ. Computer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Comparison of EfficientNet CNN models for multi-label chest X-ray disease diagnosis.PeerJ. Computer science · 2025Article
- Health Chatbots in Africa: Scoping Review.Journal of medical Internet research · 2023Article
- Artificial intelligence for differentiating COVID-19 from other viral pneumonias on CT: comparative analysis of different models based on quantitative and radiomic approaches.European radiology experimental · 2023Article
- Automatic Detection of Tuberculosis Using VGG19 with Seagull-Algorithm.Life (Basel, Switzerland) · 2022Article
- Prediction of SARS-CoV-2 infection with a Symptoms-Based model to aid public health decision making in Latin America and other low and middle income settings.Preventive medicine reports · 2022Article
- Lightweight Deep Learning Model for Assessment of Substitution Voicing and Speech after Laryngeal Carcinoma Surgery.Cancers · 2022Article
- An Ensemble Learning Model for COVID-19 Detection from Blood Test Samples.Sensors (Basel, Switzerland) · 2022Article
- A Multi-Agent Deep Reinforcement Learning Approach for Enhancement of COVID-19 CT Image Segmentation.Journal of personalized medicine · 2022Article
- Effect of neural network structure in accelerating performance and accuracy of a convolutional neural network with GPU/TPU for image analytics.PeerJ. Computer science · 2022Article
- Indirect supervision applied to COVID-19 and pneumonia classification.Informatics in medicine unlocked · 2022Article
- Ensemble Deep Learning and Internet of Things-Based Automated COVID-19 Diagnosis Framework.Contrast media & molecular imaging · 2022Article
- COV-DLS: Prediction of COVID-19 from X-Rays Using Enhanced Deep Transfer Learning Techniques.Journal of healthcare engineering · 2022Article
- An Analysis of New Feature Extraction Methods Based on Machine Learning Methods for Classification Radiological Images.Computational intelligence and neuroscience · 2022Article
- COVID-19 classification using chest X-ray images: A framework of CNN-LSTM and improved max value moth flame optimization.Frontiers in public health · 2022Article
- Tuberculosis Detection in Chest Radiographs Using Spotted Hyena Algorithm Optimized Deep and Handcrafted Features.Computational intelligence and neuroscience · 2022Article
- COVID-19 Case Recognition from Chest CT Images by Deep Learning, Entropy-Controlled Firefly Optimization, and Parallel Feature Fusion.Sensors (Basel, Switzerland) · 2021Article
- A bagging dynamic deep learning network for diagnosing COVID-19.Scientific reports · 2021Article
- Potential of artificial intelligence to accelerate diagnosis and drug discovery for COVID-19.PeerJ · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUntil now, there are still a limited number of resources available to predict and diagnose COVID-19 disease. The design of novel drug-drug interaction for COVID-19 patients is an open area of research. Also, the development of the COVID-19 rapid testing kits is still a challenging task. METHODOLOGY: This review focuses on two prime challenges caused by urgent needs to effectively address the challenges of the COVID-19 pandemic, i.e., the development of COVID-19 classification tools and drug discovery models for COVID-19 infected patients with the help of artificial intelligence (AI) based techniques such as machine learning and deep learning models.
resultsIn this paper, various AI-based techniques are studied and evaluated by the means of applying these techniques for the prediction and diagnosis of COVID-19 disease. This study provides recommendations for future research and facilitates knowledge collection and formation on the application of the AI techniques for dealing with the COVID-19 epidemic and its consequences.
conclusionsThe AI techniques can be an effective tool to tackle the epidemic caused by COVID-19. These may be utilized in four main fields such as prediction, diagnosis, drug design, and analyzing social implications for COVID-19 infected patients.
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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.