ArticleSustainable cities and society2021
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey.
Article in Sustainable cities and society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers, 5 of them syntheses that pooled it.
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Who cites it
126 citing papers in PubMed, 5 syntheses or guidelines pooled it, 484 citations in OpenAlex.
- Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review.Computer methods and programs in biomedicine · 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
- Medical image processing and COVID-19: A literature review and bibliometric analysis.Journal of infection and public health · 2022Pooled it
- Role of Artificial Intelligence in COVID-19 Detection.Sensors (Basel, Switzerland) · 2021Pooled it
- X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic.BioMed research international · 2021Pooled it
- Applications of AI/ML in accelerating the development of pulmonary drug delivery system.Acta pharmaceutica Sinica. B · 2026Review
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- Microscopic probing into plasmodesmata (PD) and PD-derived intercellular gateways (PdIGs): Beyond morphology.Protoplasma · 2026Review
- Bayesian Graphical Models for Multiscale Inference in Medical Image-Based Joint Degeneration Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- A multimodal multidomain multilingual medical foundation model for zero shot clinical diagnosis.NPJ digital medicine · 2025Article
- MLCDL: A Critical Practice and Implementation of Multi-tissue Classification and Diagnosis Using Deep Learning Algorithm.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Quantum dual-branch neural networks with transfer learning for early detection of skin cancer.American journal of translational research · 2025Article
- Fiber-Optic Sensor Spectrum Noise Reduction Based on a Generative Adversarial Network.Sensors (Basel, Switzerland) · 2024Article
- A medical multimodal large language model for future pandemics.NPJ digital medicine · 2023Article
- Visual transformer and deep CNN prediction of high-risk COVID-19 infected patients using fusion of CT images and clinical data.BMC medical informatics and decision making · 2023Article
- Discovering associations between radiological features and COVID-19 patients' deterioration.Health science reports · 2023Article
- A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media.Sensors (Basel, Switzerland) · 2023Review
- A survey of machine learning-based methods for COVID-19 medical image analysis.Medical & biological engineering & computing · 2023Review
- Bibliometric analysis of the use of artificial intelligence in COVID-19 based on scientific studies.Health science reports · 2023Article
- Boosting automatic COVID-19 detection performance with self-supervised learning and batch knowledge ensembling.Computers in biology and medicine · 2023Article
66 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many death cases and affected all sectors of human life. With gradual progression of time, COVID-19 was declared by the world health organization (WHO) as an outbreak, which has imposed a heavy burden on almost all countries, especially ones with weaker health systems and ones with slow responses. In the field of healthcare, deep learning has been implemented in many applications, e.g., diabetic retinopathy detection, lung nodule classification, fetal localization, and thyroid diagnosis. Numerous sources of medical images (e.g., X-ray, CT, and MRI) make deep learning a great technique to combat the COVID-19 outbreak. Motivated by this fact, a large number of research works have been proposed and developed for the initial months of 2020. In this paper, we first focus on summarizing the state-of-the-art research works related to deep learning applications for COVID-19 medical image processing. Then, we provide an overview of deep learning and its applications to healthcare found in the last decade. Next, three use cases in China, Korea, and Canada are also presented to show deep learning applications for COVID-19 medical image processing. Finally, we discuss several challenges and issues related to deep learning implementations for COVID-19 medical image processing, which are expected to drive further studies in controlling the outbreak and controlling the crisis, which results in smart healthy cities.
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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.