About: Interpretable artificial intelligence framework for COVID-19 screening on chest X-rays

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Interpretable artificial intelligence framework for COVID-19 screening on chest X-rays
Creator	Spandidos, Demetrios Karantanas, Apostolos Tsatsakis, Aristidis Papadakis, Georgios Vassalou, Evangelia López-González, Rafael Marias, Kostas Papanikolaou, Nikolaos Sánchez-García, Jose Trivizakis, Eleftherios Tsiknakis, Nikos
Source	Medline; PMC
abstract	COVID-19 has led to an unprecedented healthcare crisis with millions of infected people across the globe often pushing infrastructures, healthcare workers and entire economies beyond their limits. The scarcity of testing kits, even in developed countries, has led to extensive research efforts towards alternative solutions with high sensitivity. Chest radiological imaging paired with artificial intelligence (AI) can offer significant advantages in diagnosis of novel coronavirus infected patients. To this end, transfer learning techniques are used for overcoming the limitations emanating from the lack of relevant big datasets, enabling specialized models to converge on limited data, as in the case of X-rays of COVID-19 patients. In this study, we present an interpretable AI framework assessed by expert radiologists on the basis on how well the attention maps focus on the diagnostically-relevant image regions. The proposed transfer learning methodology achieves an overall area under the curve of 1 for a binary classification problem across a 5-fold training/testing dataset.
has issue date	2020-05-27(xsd:dateTime)
bibo:doi	10.3892/etm.2020.8797
bibo:pmid	32742318
has license	cc-by-nc-nd
sha1sum (hex)	c227831cafc2e6bacfd21ab0743e75f543594eb7
schema:url	https://doi.org/10.3892/etm.2020.8797
resource representing a document's title	Interpretable artificial intelligence framework for COVID-19 screening on chest X-rays
has PubMed Central identifier	PMC7388253
has PubMed identifier	32742318
schema:publication	Exp Ther Med
resource representing a document's body	covid:c227831cafc2e6bacfd21ab0743e75f543594eb7#body_text
is schema:about of	named entity 'limits' named entity 'expert' named entity 'COVID-19' named entity 'patients' named entity 'specialized' named entity 'Chest' named entity 'led' named entity 'led' named entity 'sensitivity' named entity 'diagnosis' named entity 'globe' named entity 'infrastructures' named entity 'case' named entity 'radiological imaging' named entity 'radiologists' named entity 'binary classification' named entity 'healthcare workers' named entity 'transfer learning' named entity 'neurons' named entity 'multiclass classification' named entity 'radiologists' named entity 'COVID' named entity 'vaccine' named entity 'Hyperparameter optimization' named entity 'bacteria' named entity 'source code' named entity 'COVID' named entity 'validation set' named entity 'deep learning architecture' named entity 'fatigue' named entity 'cough' named entity 'pneumonia' named entity 'ICU' named entity 'false positives' named entity 'deep neural network' named entity 'binary classification' named entity 'COVID' named entity 'Quaternary' named entity 'X-ray' named entity 'COVID-19' named entity 'bacteria' named entity 'data augmentation' named entity 'MERS' named entity 'non-specific' named entity 'transfer learning' named entity 'heatmap' named entity 'feature extraction' named entity 'validation set' named entity 'keras' named entity 'lung' named entity 'reverse transcription' named entity 'COVID' named entity 'binary classification' named entity 'ReLU function' named entity 'core 2' named entity 'viral pneumonia' named entity 'radiologists' named entity 'COVID-19' named entity 'RT-qPCR' named entity 'randomly selected' named entity 'X-rays' named entity 'Wuhan' named entity 'asymptomatic carriers' named entity 'X-ray images' named entity 'pneumonia' named entity 'pneumonia' named entity 'deep learning' named entity 'pneumonia' named entity 'COVID' named entity 'respiratory illness' named entity 'SIV'

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