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A Deep Ensemble Dynamic Learning Network for Corona Virus Disease 2019 Diagnosis.用于 2019 年冠状病毒病诊断的深度集成动态学习网络。
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Multi-branch fusion auxiliary learning for the detection of pneumonia from chest X-ray images.多分支融合辅助学习在胸部 X 射线图像肺炎检测中的应用。
Comput Biol Med. 2022 Aug;147:105732. doi: 10.1016/j.compbiomed.2022.105732. Epub 2022 Jun 15.
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A review of deep learning-based detection methods for COVID-19.基于深度学习的新型冠状病毒肺炎检测方法综述
Comput Biol Med. 2022 Apr;143:105233. doi: 10.1016/j.compbiomed.2022.105233. Epub 2022 Jan 29.
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A fuzzy-enhanced deep learning approach for early detection of Covid-19 pneumonia from portable chest X-ray images.一种用于从便携式胸部X光图像中早期检测新冠病毒肺炎的模糊增强深度学习方法。
Neurocomputing (Amst). 2022 Apr 7;481:202-215. doi: 10.1016/j.neucom.2022.01.055. Epub 2022 Jan 21.
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Multi-task vision transformer using low-level chest X-ray feature corpus for COVID-19 diagnosis and severity quantification.多任务视觉转换器利用低水平胸部 X 射线特征语料库进行 COVID-19 诊断和严重程度量化。
Med Image Anal. 2022 Jan;75:102299. doi: 10.1016/j.media.2021.102299. Epub 2021 Nov 4.
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AANet: Adaptive Attention Network for COVID-19 Detection From Chest X-Ray Images.AANet:用于从胸部 X 光图像中检测 COVID-19 的自适应注意网络。
IEEE Trans Neural Netw Learn Syst. 2021 Nov;32(11):4781-4792. doi: 10.1109/TNNLS.2021.3114747. Epub 2021 Oct 27.
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PAM-DenseNet: A Deep Convolutional Neural Network for Computer-Aided COVID-19 Diagnosis.PAM-DenseNet:一种用于计算机辅助 COVID-19 诊断的深度卷积神经网络。
IEEE Trans Cybern. 2022 Nov;52(11):12163-12174. doi: 10.1109/TCYB.2020.3042837. Epub 2022 Oct 17.
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COVID-19 Biomarkers and Advanced Sensing Technologies for Point-of-Care (POC) Diagnosis.用于即时护理(POC)诊断的COVID-19生物标志物与先进传感技术
Bioengineering (Basel). 2021 Jul 12;8(7):98. doi: 10.3390/bioengineering8070098.
9
Dual attention multiple instance learning with unsupervised complementary loss for COVID-19 screening.用于新冠肺炎筛查的具有无监督互补损失的双注意力多实例学习
Med Image Anal. 2021 Aug;72:102105. doi: 10.1016/j.media.2021.102105. Epub 2021 May 24.
10
COVID-19 Diagnostic Strategies. Part I: Nucleic Acid-Based Technologies.新型冠状病毒肺炎诊断策略。第一部分:基于核酸的技术。
Bioengineering (Basel). 2021 Apr 17;8(4):49. doi: 10.3390/bioengineering8040049.

利用医学图像的深度学习检测新型冠状病毒肺炎

Deep Learning for Detecting COVID-19 Using Medical Images.

作者信息

Liu Jia, Qi Jing, Chen Wei, Wu Yi, Nian Yongjian

机构信息

Department of Digital Medicine, School of Biomedical Engineering and Imaging Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.

Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing 400038, China.

出版信息

Bioengineering (Basel). 2022 Dec 22;10(1):19. doi: 10.3390/bioengineering10010019.

DOI:10.3390/bioengineering10010019
PMID:36671590
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9854504/
Abstract

The global spread of COVID-19 (also known as SARS-CoV-2) is a major international public health crisis [...].

摘要

新型冠状病毒肺炎(又称严重急性呼吸综合征冠状病毒2)在全球的传播是一场重大的国际公共卫生危机[……]