利用胸部x线诊断COVID-19

S. Malik, Shivendra V. Singh, Narendra Mohan Singh, Naman Panwar
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引用次数: 3

摘要

Covid-19也是一种广泛传播的感染人类的传染病。一项针对COVID-19感染患者的临床研究表明,这类患者在接触该疾病时主要是由呼吸器官感染引起的。胸部x线(即x线摄影)是一种不太复杂的成像技术,用于识别呼吸器官相关问题。深度学习是机器学习中最重要的不败技术,它为审查大量胸部x光片提供了有益的分析,这可能对Covid-19的筛查产生重大影响。在整个工作过程中,我们将covid-19感染患者的胸部x射线扫描的PA读取作为健康患者。我们使用了基于深度学习的CNN模型,并比较了它们的性能。我们对ResNeXt模型进行了等效,并检查了它们的精度,以研究模型的呈现,从Kaggle存储库中收集了6432个胸部x射线扫描样本。这项工作的核心是聚集性covid-19感染患者的潜在途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnosis of COVID-19 Using Chest X-ray
Covid-19 is also a wide spreading infective agent disease that infects humans. A clinical study of COVID-19 infected patients has shown that these kinds of patients are square measure principally infected from a respiratory organ infection when come in contact with this disease. Chest xray (i.e., radiography) a less complicated imaging technique for identification respiratory organ connected issues. Deep learning is that the foremost undefeated technique of machine learning, that provides helpful analysis to review an oversize quantity of chest x-ray pictures which may critically impact on screening of Covid-19. Throughout this work, we have taken the PA read of chest x-ray scans for covid-19 affected patients conjointly as healthy patients. We have used deep learning-based CNN models and compared their performance. We have equate ResNeXt models and inspect their precision to investigate the model presentation, 6432 chest x-ray scans samples square measure collected from the Kaggle repository. This work solely core on potential ways of cluster covid-19 infected patients.
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