COVID - 19数据分析的深度学习算法

J. Yogapriya
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摘要

Covid-19是一种迅速影响人类的病毒性疾病,死亡率也日益增加。最近发现了一种针对COVID-19的疫苗,并由特定年龄的人群使用。有不同类型的测试被用来确定一个人是否患有冠状病毒。主要是肺部受到人的影响,不能连续呼吸。对于弓步相关疾病的诊断,胸部x线和胸部CT成像技术被广泛使用。目前正在进行各种研究,以通过胸部X射线图像识别冠状病毒。尽管如此,与胸部CT相比,胸部x光检查的成本更低。深度学习技术正在应用于分析大量可以筛查新冠病毒的胸部x光图像。本文分析了利用胸部x线图像识别冠状病毒症状的各种深度学习技术。卷积神经网络算法对新冠肺炎和正常患者的分析准确率达到95%。©2021卡拉德尼兹技术大学。版权所有。
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Deep learning algorithms for COVID 19 data analytics
Covid-19 is a viral disease that affects the humans very fastly where by the death rate also increasing day by day. Recently a vaccine for COVID-19 is identified and being used by a particular age of people. There are different types of tests are being used to identify whether a person is having a corona or not. Mainly, the lung is being affected by people and unable to breath continuously. For diagnosing lunge related problems, Chest x-ray and chest CT imaging techniques are widely used. Various researches are being conducted to identify corona virus by using chest X ray images. Still, a substantial chest x-ray is a lower cost process in comparison to chest CT. Deep Learning techniques are being applied for analyzing a large amount of chest x-ray images which could screen the COVID-19.This paper analysis the various deep learning techniques applied for identifying corona virus symptoms using chest x ray images. Convolutional Neural Network algorithm has achieved 95% accuracy for analyzing COVID 19 and Normal patients. © 2021 Karadeniz Technical University. All rights reserved.
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