Detecting SARS-CoV-2 From Chest X-Ray Using Artificial Intelligence

Chest radiographs (X-rays) combined with Deep Convolutional Neural Network (CNN) methods have been demonstrated to detect and diagnose the onset of COVID-19, the disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). However, questions remain regarding the accuracy of th...

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Veröffentlicht in:	IEEE access 2021-01, Vol.9, p.35501-35513
Hauptverfasser:	Ahsan, Md Manjurul, Ahad, Md Tanvir, Soma, Farzana Akter, Paul, Shuva, Chowdhury, Ananna, Luna, Shahana Akter, Yazdan, Munshi Md. Shafwat, Rahman, Akhlaqur, Siddique, Zahed, Huebner, Pedro
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial intelligence Artificial neural networks Biomedical Engineering Chest chest X-ray Computed tomography Confidence intervals coronavirus Coronaviruses COVID-19 Data models Datasets Deep learning Diseases Imaging imbalanced data Lung Radiographs SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 Signs and symptoms small data Viral diseases X-ray imaging X-rays
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