Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images-Reference-Cited by-同舟云学术

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Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images

Published:2021-01-15 Issue:1 Volume:27 Page:20-27
ISSN:1305-3612
Container-title:Diagnostic and Interventional Radiology
language:
Short-container-title:Diagn Interv Radiol

Author:

Blain Maxime, ,Kassin Michael T.,Varble Nicole,Wang Xiaosong,Xu Ziyue,Xu Daguang,Carrafiello Gianpaolo,Vespro Valentina,Stellato Elvira,Ierardi Anna Maria,Di Meglio Letizia,Suh Robert D.,Walker Stephanie A.,Xu Sheng,Sanford Thomas H.,Turkbey Evrim B.,Harmon Stephanie,Turkbey Baris,Wood Bradford J., , , , , , , , , , , , , , , , , , , , , , , , ,

Publisher

AVES Publishing Co.

Subject

Cardiology and Cardiovascular Medicine,Radiology, Nuclear Medicine and imaging

Cited by 52 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. COVID-19 severity detection using chest X-ray segmentation and deep learning;Scientific Reports;2024-08-27

2. A High-Performance CNN Hardware Accelerator for Covid-19 Feature Extraction from X-ray Images;2024 9th International Conference on Integrated Circuits, Design, and Verification (ICDV);2024-06-06

3. Augmentation strategies for an imbalanced learning problem on a novel COVID-19 severity dataset;Scientific Reports;2023-10-25

4. Automatic diagnosis of COVID-19 from CT images using CycleGAN and transfer learning;Applied Soft Computing;2023-09

5. Artificial intelligence and machine learning responses to COVID-19 related inquiries;Journal of Medical Engineering & Technology;2023-08-18

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