{"title":"covid - code:使用卷积神经网络从胸部x射线图像中检测COVID-19","authors":"Rishabh Raj","doi":"10.46501/ijmtst061283","DOIUrl":null,"url":null,"abstract":"ommand, product recommendation and medical diagnosis. The detection of severe acute respiratory\nsyndrome corona virus 2 (SARS CoV-2), which is responsible for corona virus disease 2019 (COVID-19),\nusing chest X-ray images has life-saving importance for bothpatients and doctors. In addition, in countries\nthat are unable to purchase laboratory kits for testing, this becomes even more vital. In this study, we aimed\nto present the use of deep learning for the high-accuracy detection of COVID-19 using chest X-ray images.\nPublicly available X-ray images were used in the experiments, which involved the training of deep learning\nand machine learning classifiers. Experiments were performed using convolutional neural networks and\nmachine learning models. Images and statistical data were considered separately in the experiments to\nevaluate the performances of models, and eightfold cross-validation was used. A mean accuracy of 98.50%.\nA convolutional neural network without pre-processing and with minimized layers is capable of detecting\nCOVID- 19 in a limited number of, and in imbalanced, chest X-rayimages.","PeriodicalId":13741,"journal":{"name":"International Journal for Modern Trends in Science and Technology","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CoviDecode : Detection of COVID-19 from Chest\\nX-Ray images using Convolutional Neural\\nNetworks\",\"authors\":\"Rishabh Raj\",\"doi\":\"10.46501/ijmtst061283\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ommand, product recommendation and medical diagnosis. The detection of severe acute respiratory\\nsyndrome corona virus 2 (SARS CoV-2), which is responsible for corona virus disease 2019 (COVID-19),\\nusing chest X-ray images has life-saving importance for bothpatients and doctors. In addition, in countries\\nthat are unable to purchase laboratory kits for testing, this becomes even more vital. In this study, we aimed\\nto present the use of deep learning for the high-accuracy detection of COVID-19 using chest X-ray images.\\nPublicly available X-ray images were used in the experiments, which involved the training of deep learning\\nand machine learning classifiers. Experiments were performed using convolutional neural networks and\\nmachine learning models. Images and statistical data were considered separately in the experiments to\\nevaluate the performances of models, and eightfold cross-validation was used. A mean accuracy of 98.50%.\\nA convolutional neural network without pre-processing and with minimized layers is capable of detecting\\nCOVID- 19 in a limited number of, and in imbalanced, chest X-rayimages.\",\"PeriodicalId\":13741,\"journal\":{\"name\":\"International Journal for Modern Trends in Science and Technology\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal for Modern Trends in Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46501/ijmtst061283\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal for Modern Trends in Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46501/ijmtst061283","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CoviDecode : Detection of COVID-19 from Chest
X-Ray images using Convolutional Neural
Networks
ommand, product recommendation and medical diagnosis. The detection of severe acute respiratory
syndrome corona virus 2 (SARS CoV-2), which is responsible for corona virus disease 2019 (COVID-19),
using chest X-ray images has life-saving importance for bothpatients and doctors. In addition, in countries
that are unable to purchase laboratory kits for testing, this becomes even more vital. In this study, we aimed
to present the use of deep learning for the high-accuracy detection of COVID-19 using chest X-ray images.
Publicly available X-ray images were used in the experiments, which involved the training of deep learning
and machine learning classifiers. Experiments were performed using convolutional neural networks and
machine learning models. Images and statistical data were considered separately in the experiments to
evaluate the performances of models, and eightfold cross-validation was used. A mean accuracy of 98.50%.
A convolutional neural network without pre-processing and with minimized layers is capable of detecting
COVID- 19 in a limited number of, and in imbalanced, chest X-rayimages.