COVID19XrayNet: A Two-Step Transfer Learning Model for the COVID-19 Detecting Problem Based on a Limited Number of Chest X-Ray Images - Zhang, Ruochi; Guo, Zhehao; Sun, Yue; Lu, Qi; Xu, Zijian; Yao, Zhaomin; Duan, Meiyu; Liu, Shuai; Ren, Yanjiao; Huang, Lan; Zhou, Fengfeng (Interdisciplinary sciences : computational life sciences, 2020)
Keywords: Algorithms; Artificial neural networks; Betacoronavirus; Biomedical and Life Sciences; Chest; Clinical Laboratory Techniques - methods; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Appl. in Life Sciences; Coronaviridae; Coronavirus; Coronavirus Infections - complications; Coronavirus Infections - diagnosis; Coronavirus Infections - diagnostic imaging; Coronavirus Infections - virology; Coronaviruses; COVID-19; COVID-19 Testing; Databases, Factual; Datasets; Datasets as Topic; Deep Learning; Diagnostic systems; Health Sciences; Humans; Life Sciences; Lung - diagnostic imaging; Lung diseases; Machine Learning; Mathematical and Computational Physics; Medical imaging; Medicine; Model accuracy; Models, Biological; Neural networks; Neural Networks, Computer; Pandemics; Pneumonia - diagnosis; Pneumonia - diagnostic imaging; Pneumonia - etiology; Pneumonia - virology; Pneumonia, Viral - complications; Pneumonia, Viral - diagnosis; Pneumonia, Viral - diagnostic imaging; Pneumonia, Viral - virology; Radiography - methods; Reference Values; SARS-CoV-2; Severe acute respiratory syndrome coronavirus 2; Short Communication; Statistics for Life Sciences; Theoretical; Theoretical and Computational Chemistry; Tomography, X-Ray Computed - methods; Training; Transfer learning; Viral diseases; X ray imagery; X-Rays; Feature smoothing layer (FSL); ResNet34; Two-step transfer learning; Feature extraction layer (FEL); COVID19XrayNet