About: covid:PMC7303695

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An Entity of Type : owl:Thing, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
Creator	Sloot, Peter Teixeira, João Dongarra, Jack Alves, Domingos Andrade Bernardi, Filipe Brissos, Sérgio Colombo Filho, Márcio Koenigkam Santos, Marcel Kritski, Afrânio Krzhizhanovskaya, Valeria Lees, Michael Mello Galliez, Rafael Závodszky, Gábor de Oliveira, Lariza
is schema:about of	named entity 'Detection' named entity 'DETECTION' named entity 'Convolutional Neural Networks' named entity 'Chest X-Ray' named entity 'lungs' named entity 'Turbo Boost' named entity 'Keras' named entity 'radiologists' named entity 'computer-aided diagnosis' named entity 'HIV status' named entity 'Colab' named entity 'hyperthreaded' named entity 'Brazil' named entity 'tuberculosis' named entity 'backpropagation' named entity 'TB control' named entity 'Google' named entity 'CXR' named entity '0.9' named entity 'triage' named entity 'global health emergency' named entity 'epidemic' named entity 'bacteria' named entity 'data augmentation' named entity 'GoogLeNet' named entity 'Receiver Operating Characteristic' named entity 'CXR' named entity 'CXR' named entity 'triage' named entity '10 million' named entity 'screening tool' named entity 'diagnostic aid' named entity 'diagnostic accuracy' named entity 'mycobacterium tuberculosis complex' named entity 'CUDA' named entity 'digital health' named entity 'ResNet' named entity 'respiratory complications' named entity 'Google Docs' named entity 'TB treatment' named entity 'WHO' named entity 'asymptomatic' named entity 'AlexNet' named entity 'HDF5' named entity 'Shenzhen' named entity 'CNN' named entity 'US Food and Drug Administration' named entity 'triage' named entity 'pulmonary tuberculosis' named entity 'convolutional neural network' named entity 'confusion matrix' named entity 'class function' named entity 'neurons' named entity 'NIH' named entity 'AlexNet' named entity 'tuberculosis' named entity 'false positive rate' named entity 'HIV' named entity 'true positive rate' named entity 'public health' named entity 'TensorFlow' named entity 'epidemic' named entity 'chest X-ray' named entity 'Google Drive' named entity '0.9' named entity '0.01' named entity 'triage' named entity 'Matplotlib' named entity 'batch normalization' named entity 'HIV-negative' named entity 'hominids' named entity 'Colab' named entity 'systematic reviews' named entity 'CXR' named entity 'binary classifier' named entity 'Montgomery County, Maryland' named entity 'diagnostic accuracy' named entity 'SGD' named entity 'infectious agent' named entity 'WHO' named entity 'ROC curve' named entity 'Tuberculosis' named entity 'WHO' named entity 'CAD program' named entity 'data set' named entity 'WHO'

Attributes

Values

Creator

Sloot, Peter
Teixeira, João
Dongarra, Jack
Alves, Domingos
Andrade Bernardi, Filipe
Brissos, Sérgio
Colombo Filho, Márcio
Koenigkam Santos, Marcel
Kritski, Afrânio
Krzhizhanovskaya, Valeria
Lees, Michael
Mello Galliez, Rafael
Závodszky, Gábor
de Oliveira, Lariza

is schema:about of

named entity 'Detection'
named entity 'DETECTION'
named entity 'Convolutional Neural Networks'
named entity 'Chest X-Ray'
named entity 'lungs'
named entity 'Turbo Boost'
named entity 'Keras'
named entity 'radiologists'
named entity 'computer-aided diagnosis'
named entity 'HIV status'
named entity 'Colab'
named entity 'hyperthreaded'
named entity 'Brazil'
named entity 'tuberculosis'
named entity 'backpropagation'
named entity 'TB control'
named entity 'Google'
named entity 'CXR'
named entity '0.9'
named entity 'triage'
named entity 'global health emergency'
named entity 'epidemic'
named entity 'bacteria'
named entity 'data augmentation'
named entity 'GoogLeNet'
named entity 'Receiver Operating Characteristic'
named entity 'CXR'
named entity 'CXR'
named entity 'triage'
named entity '10 million'
named entity 'screening tool'
named entity 'diagnostic aid'
named entity 'diagnostic accuracy'
named entity 'mycobacterium tuberculosis complex'
named entity 'CUDA'
named entity 'digital health'
named entity 'ResNet'
named entity 'respiratory complications'
named entity 'Google Docs'
named entity 'TB treatment'
named entity 'WHO'
named entity 'asymptomatic'
named entity 'AlexNet'
named entity 'HDF5'
named entity 'Shenzhen'
named entity 'CNN'
named entity 'US Food and Drug Administration'
named entity 'triage'
named entity 'pulmonary tuberculosis'
named entity 'convolutional neural network'
named entity 'confusion matrix'
named entity 'class function'
named entity 'neurons'
named entity 'NIH'
named entity 'AlexNet'
named entity 'tuberculosis'
named entity 'false positive rate'
named entity 'HIV'
named entity 'true positive rate'
named entity 'public health'
named entity 'TensorFlow'
named entity 'epidemic'
named entity 'chest X-ray'
named entity 'Google Drive'
named entity '0.9'
named entity '0.01'
named entity 'triage'
named entity 'Matplotlib'
named entity 'batch normalization'
named entity 'HIV-negative'
named entity 'hominids'
named entity 'Colab'
named entity 'systematic reviews'
named entity 'CXR'
named entity 'binary classifier'
named entity 'Montgomery County, Maryland'
named entity 'diagnostic accuracy'
named entity 'SGD'
named entity 'infectious agent'
named entity 'WHO'
named entity 'ROC curve'
named entity 'Tuberculosis'
named entity 'WHO'
named entity 'CAD program'
named entity 'data set'
named entity 'WHO'

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