COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest Radiography Images

By Linda Wang, Alexander Wong. arXiv.org, 2020

588 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/891be639a4db04eb28b3179fc1fb040dd90d0bc9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

COVIDiagnosis-Net: Deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from X-ray images (2020, unknown): “For this motivation, there are several studies in the literature including the analysis conducted on AI-based diagnostic of the COVID-19 with the help of the radiological images [11-15].”
COVID_MTNet: COVID-19 Detection with Multi-Task Deep Learning Approaches (2020, methodology): “The proposed pneumonia detection method shows around 87.26% testing accuracy whereas the recently published paper in [15] shows 84.67% testing accuracy.”
Automated detection of COVID-19 cases using deep neural networks with X-ray images (2020, methodology): “Few studies conducted prior to this study have used 25 and 50 images in each class [41,42,44,45].”
COVID-ResNet: A Deep Learning Framework for Screening of COVID19 from Radiographs (2020, methodology): “We used the COVIDx dataset that was recently made public by the authors of the COVID-Net [7].”
Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts (2020, methodology): “in chest radiography images, the authors in [47] tries to design a deep convolutional neural network (CNN) model for the detection of COVID-19 cases.”
COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios (2020, unknown): “Wang and Wong [41] created the COVID-Net, an open source deep neural network specially created aiming to detect COVID-19 on chest radiography images.”
Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets (2020, methodology): “By combining with our novel preprocessing step to normalize the data heterogeneities and bias, we demonstrate that the proposed network architecture provides better sensitivity and interpretability, compared to the existing COVID-Net [6] with the same data set.”
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey (2020, unknown): “This screening tool was developed using almost 6000 image datasets of chest radiography images collected from 3000 patients (Ozturk et al., 2020; Wang & Wong, 2020).”
Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks (2020, unknown): “Wang et al. [33] , obtained a classiﬁcation accuracy of 89.50% using the Inception-Net deep learning model with CT images.”
AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app (2020, unknown): “Furthermore, AI-based analyses of X-ray [14]–[17] and CT scan [27], [28] of the respiratory system have also shown to exploit the differences in pathomorphological alternations caused by COVID-19 to perform differential diagnosis among bacterial infection, non-COVID-19 viral infection and COVID-19 v”
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19 (2020, methodology): “Chest X-ray and CT are widely used in the screening and diagnosis of COVID-19 [6-11].”
Automatic Detection of Coronavirus Disease (COVID-19) in X-ray and CT Images: A Machine Learning Based Approach (2020, unknown): “Wang and Wong [18] designed a tailored deep learning-based framework, COVID-Net, developed for COVID-19 detection from chest X-ray images.”
A review of modern technologies for tackling COVID-19 pandemic (2020, unknown): “COVID-Net an arti ﬁ cial intelligence application is created to analyze COVID-19 symptoms in chest x-rays utilizing information of different lung conditions and COVID-19 from patients [10].”
Artificial intelligence vs COVID-19: limitations, constraints and pitfalls (2020, background): “Representative contributions in this regard include Chen et al. (2020b) and Wang and Wong (2020).”
Explainable Deep Learning Models in Medical Image Analysis (2020, methodology): “GSInquire, GBP, activation maps [47] COVIDNet CNN COVID-19 detection X-ray images”
COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm (2020, background): “In Wang and Wong (9) researchers have implemented a Convolutional Neural Network based model to detect COVID-19 patients using CXR images.”
A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2 (2020, unknown): “COVID-Net uses a lightweight residual projection-expansion- projection-extension (PEPX) design pattern to investigate quantitative analysis and qualitative analysis [18].”