About: AI based Chest X-Ray (CXR) Scan Texture Analysis Algorithm for Digital Test of COVID-19 Patients

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	AI based Chest X-Ray (CXR) Scan Texture Analysis Algorithm for Digital Test of COVID-19 Patients
Creator	Al-Karawi, Dhurgham Al-Zaidi, Shakir Jassim, Sabah Polus, Nisreen
Source	MedRxiv
abstract	Chest Imaging in COVID-19 patient management is becoming an essential tool for controlling the pandemic that is gripping the international community. It is already indicated in patients with COVID-19 and worsening respiratory status. The rapid spread of the pandemic to all continents, albeit with a nonuniform community transmission, necessitates chest imaging for medical triage of patients presenting moderate-severe clinical COVID-19 features. This paper reports the development of innovative machine learning schemes for the analysis of Chest X-Ray (CXR) scan images of COVID-19 patients in almost real-time, demonstrating significantly high accuracy in identifying COVID-19 infection. The performance testing was conducted on a combined dataset comprising CXRs of positive COVID-19 patients, patients with various viral and bacterial infections, as well as persons with a clear chest. The test resulted in successfully distinguishing CXR COVID-19 infection from the other cases with an average accuracy of 94.43%, sensitivity 95% and specificity 93.86%.
has issue date	2020-05-08(xsd:dateTime)
bibo:doi	10.1101/2020.05.05.20091561
has license	medrxiv
sha1sum (hex)	e97b59dc2293445fa5c75693ac85a23c3e253b0f
schema:url	https://doi.org/10.1101/2020.05.05.20091561
resource representing a document's title	AI based Chest X-Ray (CXR) Scan Texture Analysis Algorithm for Digital Test of COVID-19 Patients
resource representing a document's body	covid:e97b59dc2293445fa5c75693ac85a23c3e253b0f#body_text
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