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Original Research

Novel Deep Learning Technique Used in Management and Discharge of Hospitalized Patients with COVID-19 in China

ORCID Icon, , ORCID Icon, , , , & ORCID Icon show all
Pages 1195-1201 | Published online: 08 Dec 2020

References

  • Perlman S. Another decade, another coronavirus. N Engl J Med. 2020;382(8):760–762. doi:10.1056/NEJMe2001126.
  • Richman DD, Whitley RJ, Hayden FG, eds. Clinical Virology, 4th Edn. Washington: ASM Press; 2016.
  • Zhu N, Zhang D, Wang W, et al. China Novel Coronavirus Investigating and Research Team. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med. 2020;382(8):727–733. doi:10.1056/NEJMoa2001017.
  • Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506. doi:10.1016/S0140-6736(20)30183-5.
  • Wang D, Hu B, Hu C, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China. JAMA. 2020;323(11):1061–1069. doi:10.1001/jama.2020.1585
  • National Health Commission of the People’s Republic of China website. Diagnosis and treatment of novel coronavirus infection (trial version6); 2020. Avialble from: www.nhc.gov.cn/yzygj/s7653p/202002/8334a8326dd94d329df351d7da8aefc2.shtml. Accessed February 19, 2020.
  • Li Y, Xia XL. Coronavirus Disease 2019 (COVID-19): role of Chest CT in Diagnosis and Management. AJR Am J Roentgenol. 2020;214(6):1280–1286. doi:10.2214/AJR.20.22954.
  • Kong B, Wang X, Bai J, et al. Learning tree-structured representation for 3D coronary artery segmentation. Comput Med Imaging Graph. 2020;80:101688. doi:10.1016/j.compmedimag.2019.101688.
  • Ye H, Gao F, Yin Y, et al. Precise diagnosis of intracranial hemorrhage and subtypes using a threedimensional joint convolutional and recurrent neural network. Eur Radiol. 2019;29:6191–6201. doi:10.1007/s00330-019-06163-2
  • Li Z, Zhong Z, Li Y, et al. From community-acquired pneumonia to COVID-19: a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans. Eur Radiol. 2020:1–10. doi:10.1007/s00330-020-07042-x.
  • Ren S, He K, Girshick R, Sun J. Faster R-CNN: towards Real-Time Object Detection with Region Proposal Networks. IEEE Trans Pattern Anal Mach Intell. 2017;39(6):1137–1149. doi:10.1109/TPAMI.2016.2577031.
  • Ding J, Li A, Hu Z, Wang L. Accurate pulmonary nodule detection in computed tomography images using deep convolutional neural networks. In: Descoteaux M, Maier-Hein L, Franz A, Jannin P, Collins DL, Duchesne S, editors. International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham; 2017:pp. 559–567.
  • Ronneberger O, Philipp F, Thomas B. U-Net: Convolutional Networks for Biomedical Image Segmentation. International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham; 2015.
  • Tian S, Hu W, Niu L, Liu H, Xu H, Xiao S-Y. Pulmonary Pathology of Early-Phase 2019 Novel Coronavirus (COVID-19) Pneumonia in Two Patients With Lung Cancer. J Thorac Oncol. 2020;15(5):700–704. doi:10.1016/j.jtho.2020.02.010.
  • Xu Z, Shi L, Wang Y, et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 2020;8(4):420–422. doi:10.1016/S2213-2600(20)30076-X.
  • Hansell DM, Bankier AA, MacMahon H, et al. Fleischner Society: glossary of terms for thoracic imaging. Radiology. 2008;246(3):697–722. doi:10.1148/radiol.2462070712.
  • Rajaraman S, Candemir S, Xue Z, et al. A Novel Stacked Generalization of Models for Improved TB Detection in Chest Radiographs. Conf Proc IEEE Eng Med Biol Soc. 2018:718–721. doi:10.1109/EMBC.2018.8512337
  • Shi H, Han X, Jiang N, et al. Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. Lancet Infect Dis. 2020;20(4):425–434. doi:10.1016/S1473-3099(20)30086-4.