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Deep Learning Based Chest X-Ray Image as a Diagnostic Tool for COVID-19

机译:基于深度学习的胸部X射线图像作为COVID-19的诊断工具

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The COVID-19 pandemic has a rapid spread across the globe, which has deployed life threatening complications ever since it started from China in December 2019. A quick detection of positive cases on corona virus will prevent the further community spread and initiates a earlier treatment to common man. In Recent findings, the images of Chest X ray and CT scan have shown salient features that illustrates the severity of corona virus in lungs. Scientific advancement of Artificial Intelligence in deploying a deep learning based medical field is remaining powerful to handle a huge data with accurate and fast results in medical imaging to diagnose diseases more accurately and efficiently with further assistance in the remote areas. Proposed method is developed for analyzing chest X ray images to detect COVID-19 for binary classes with an accuracy of 99% and validation accuracy of 98%, where the loss is approximately 0.15% by using convolution 2D techniques that are applied on the open source datasets of COVID-19 available at GitHub and Kaggle.
机译:自2019年12月从中国爆发以来,COVID-19大流行在全球范围内迅速蔓延,已经部署了危及生命的并发症。快速检测到冠状病毒阳性病例将防止社区进一步蔓延,并提早进行治疗。普通人。在最近的发现中,胸部X射线和CT扫描的图像显示出明显的特征,这些特征说明了肺部冠状病毒的严重性。人工智能在部署基于深度学习的医学领域中的科学进步仍然具有强大的功能,可以在医学成像中快速准确地处理海量数据,从而在偏远地区的进一步协助下更准确,更有效地诊断疾病。开发了一种用于分析胸部X射线图像以检测二进制类别的COVID-19的方法,其准确度为99%,验证准确度为98%,其中使用在开源上应用的卷积2D技术,损失约为0.15%可以从GitHub和Kaggle获得COVID-19的数据集。

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