使用深度学习进行COVID-19和肺部疾病检测

Manali Shukla, B. Tripathi, Malti Nagle, B. Chaurasia
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引用次数: 5

摘要

2019冠状病毒病(COVID-19)是一种传染病。本文提出了一种基于深度学习的COVID-19疾病检测方法。新型冠状病毒对人群的影响是多方面的。病毒呈指数级增长,缺乏治疗知识是医生拯救患者生命的最大挑战。由于呼吸机和ICU临床试验和测试的可用性较少,COVID-19健康状况超负荷。通过胸部x线诊断肺部感染是检测COVID-19严重程度的最佳和最快方法。本文提出了一种通过胸部x线报告诊断检测新冠肺炎的人工智能模型。胸部x线报告发现采用CNN(卷积神经网络)模型,结合ResNet50和VGG 19模型。该模型将患者分为新冠肺炎、正常、肺炎、肺型肥胖四类。AI模型通过图像处理方法训练x射线图像,准确率达到99.3%。本文还从准确性、特异性、敏感性、精密度等方面分析了该模型的有效性。
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COVID-19 & Lung Disease Detection using Deep Learning
Corona virus disease 2019 (COVID-19) is an infectious disease. We have proposed a COVID-19 disease detection using deep learning method in this paper. Novel disease coronavirus bring forth diverse effect on population. Exponential growth of virus and lack of knowledge of treatment was the biggest challenge for doctors to save patient's life. Due to less availability of ventilator and ICU clinical trial and testing overloaded of COVID-19 health status. Lung infection diagnosed by Chest X-ray found as best and fastest approach to detect severity of COVID-19. The work presents an AI model to detect the COVID-19 by diagnoses of chest X-ray report. Chest X-ray report finding has been conducted using CNN (convolution neural network) model with ResNet50 and VGG 19 model. The model classify the patients into four category COVID-19, normal, pneumonia, lung obesity. AI model train the X-ray image through image processing methods with an accuracy of 99.3%. The efficacy of proposed model also has been analyzed in terms of accuracy, specificity, and sensitivity, precision.
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