Artificial Intelligence–assisted chest X-ray assessment scheme for COVID-19

Objectives To study whether a trained convolutional neural network (CNN) can be of assistance to radiologists in differentiating Coronavirus disease (COVID)–positive from COVID-negative patients using chest X-ray (CXR) through an ambispective clinical study. To identify subgroups of patients where a...

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Veröffentlicht in:	European radiology 2021-08, Vol.31 (8), p.6039-6048
Hauptverfasser:	Rangarajan, Krithika, Muku, Sumanyu, Garg, Amit Kumar, Gabra, Pavan, Shankar, Sujay Halkur, Nischal, Neeraj, Soni, Kapil Dev, Bhalla, Ashu Seith, Mohan, Anant, Tiwari, Pawan, Bhatnagar, Sushma, Bansal, Raghav, Kumar, Atin, Gamanagati, Shivanand, Aggarwal, Richa, Baitha, Upendra, Biswas, Ashutosh, Kumar, Arvind, Jorwal, Pankaj, Shalimar, Shariff, A., Wig, Naveet, Subramanium, Rajeshwari, Trikha, Anjan, Malhotra, Rajesh, Guleria, Randeep, Namboodiri, Vinay, Banerjee, Subhashis, Arora, Chetan
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial Intelligence Artificial neural networks Chest Coronaviruses COVID-19 Diagnostic Radiology Heart Humans Imaging Imaging Informatics and Artificial Intelligence Internal Medicine Interventional Radiology Medicine Medicine & Public Health Neural networks Neuroradiology Patients Polymerase chain reaction Predictions Radiographs Radiography Radiography, Thoracic Radiology Recall RNA-directed DNA polymerase SARS-CoV-2 Subgroups Tomography, X-Ray Computed Ultrasound Viral diseases X-Rays
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