ArticleIEEE access : practical innovations, open solutions2020
Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment.
Article in IEEE access : practical innovations, open solutions, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 133 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
133 citing papers in PubMed, 2 syntheses or guidelines pooled it, 548 citations in OpenAlex.
- Occam's razor or Hickam's dictum-COVID-19 is not a textbook aetiology of acute pancreatitis: A modified Naranjo Score appraisal.World journal of gastroenterology · 2023Pooled it
- Biomedical application, drug delivery and metabolic pathway of antiviral nanotherapeutics for combating viral pandemic: A review.Environmental research · 2020Pooled it
- Comparative review of artificial intelligence for transcriptomic biomarker discovery in coronavirus disease 2019 (COVID-19).Briefings in bioinformatics · 2026Review
- Article
- The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.Molecular biomedicine · 2025Review
- Explainable Encoder-Prediction-Reconstruction Framework for the Prediction of Metasurface Absorption Spectra.Nanomaterials (Basel, Switzerland) · 2024Article
- Navigating the Metaverse: A New Virtual Tool with Promising Real Benefits for Breast Cancer Patients.Journal of clinical medicine · 2024Review
- DNA encoding schemes herald a new age in cybersecurity for safeguarding digital assets.Scientific reports · 2024Article
- Article
- Hybrid disease prediction approach leveraging digital twin and metaverse technologies for health consumer.BMC medical informatics and decision making · 2024Article
- Review
- CoSev: Data-Driven Optimizations for COVID-19 Severity Assessment in Low-Sample Regimes.Diagnostics (Basel, Switzerland) · 2024Article
- A methodical exploration of imaging modalities from dataset to detection through machine learning paradigms in prominent lung disease diagnosis: a review.BMC medical imaging · 2024Review
- Deep Learning in Heart Sound Analysis: From Techniques to Clinical Applications.Health data science · 2024Review
- An architecture for COVID-19 analysis and detection using big data, AI, and data architectures.PloS one · 2024Article
- Article
- An Innovative Solution Based on TSCA-ViT for Osteosarcoma Diagnosis in Resource-Limited Settings.Biomedicines · 2023Article
- Automatic diagnosis of COVID-19 from CT images using CycleGAN and transfer learning.Applied soft computing · 2023Article
- Utilization of Deep Convolutional Neural Networks for Accurate Chest X-Ray Diagnosis and Disease Detection.Interdisciplinary sciences, computational life sciences · 2023Article
- A Systematic Review on Deep Structured Learning for COVID-19 Screening Using Chest CT from 2020 to 2022.Healthcare (Basel, Switzerland) · 2023Review
73 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors at 14 institutions in 8 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spread in 212 countries and territories and increasing numbers of infected cases and death tolls mounting to 5,212,172 and 334,915 (as of May 22 2020), it remains a real threat to the public health system. This paper renders a response to combat the virus through Artificial Intelligence (AI). Some Deep Learning (DL) methods have been illustrated to reach this goal, including Generative Adversarial Networks (GANs), Extreme Learning Machine (ELM), and Long/Short Term Memory (LSTM). It delineates an integrated bioinformatics approach in which different aspects of information from a continuum of structured and unstructured data sources are put together to form the user-friendly platforms for physicians and researchers. The main advantage of these AI-based platforms is to accelerate the process of diagnosis and treatment of the COVID-19 disease. The most recent related publications and medical reports were investigated with the purpose of choosing inputs and targets of the network that could facilitate reaching a reliable Artificial Neural Network-based tool for challenges associated with COVID-19. Furthermore, there are some specific inputs for each platform, including various forms of the data, such as clinical data and medical imaging which can improve the performance of the introduced approaches toward the best responses in practical applications.
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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.