图像处理技术及其在决策支持系统中应用卷积神经网络进行Covid-19疾病预测的性能分析

K. Ravishankar, C. Jothikumar
{"title":"图像处理技术及其在决策支持系统中应用卷积神经网络进行Covid-19疾病预测的性能分析","authors":"K. Ravishankar, C. Jothikumar","doi":"10.1093/comjnl/bxac154","DOIUrl":null,"url":null,"abstract":"\n The Covid-19 pandemic has been identified as a key issue for human society, in recent times. The presence of the infection on any human is identified according to different symptoms like cough, fever, headache, breathless and so on. However, most of the symptoms are shared by various other diseases, which makes it challenging for the medical practitioners to identify the infection. To aid the medical practitioners, there are a number of approaches designed which use different features like blood report, lung and cardiac features to detect the disease. The method captures the lung image using magnetic resonance imaging scan device and records the cardiac features. Using the image, the lung features are extracted and from the cardiac graph, the cardiac features are extracted. Similarly, from the blood samples, the features are extracted. By extracting such features from the person, the method estimates different weight measures to predict the disease. Different methods estimate the similarity of the samples in different ways to classify the input sample. However, the image processing techniques are used for different problems in medical domain; the same has been used in the detection of the disease. Also, the presence of Covid-19 is detected using different set of features by various approaches.","PeriodicalId":21872,"journal":{"name":"South Afr. Comput. J.","volume":"238 1","pages":"1030-1039"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis Performance Of Image Processing Technique Its Application by Decision Support Systems On Covid-19 Disease Prediction Using Convolution Neural Network\",\"authors\":\"K. Ravishankar, C. Jothikumar\",\"doi\":\"10.1093/comjnl/bxac154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n The Covid-19 pandemic has been identified as a key issue for human society, in recent times. The presence of the infection on any human is identified according to different symptoms like cough, fever, headache, breathless and so on. However, most of the symptoms are shared by various other diseases, which makes it challenging for the medical practitioners to identify the infection. To aid the medical practitioners, there are a number of approaches designed which use different features like blood report, lung and cardiac features to detect the disease. The method captures the lung image using magnetic resonance imaging scan device and records the cardiac features. Using the image, the lung features are extracted and from the cardiac graph, the cardiac features are extracted. Similarly, from the blood samples, the features are extracted. By extracting such features from the person, the method estimates different weight measures to predict the disease. Different methods estimate the similarity of the samples in different ways to classify the input sample. However, the image processing techniques are used for different problems in medical domain; the same has been used in the detection of the disease. Also, the presence of Covid-19 is detected using different set of features by various approaches.\",\"PeriodicalId\":21872,\"journal\":{\"name\":\"South Afr. Comput. J.\",\"volume\":\"238 1\",\"pages\":\"1030-1039\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South Afr. Comput. J.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/comjnl/bxac154\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South Afr. Comput. J.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/comjnl/bxac154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

近年来,新冠肺炎疫情已成为人类社会面临的重大问题。根据不同的症状,如咳嗽、发烧、头痛、上气不接下气等,可以确定任何人是否受到感染。然而,大多数症状是由各种其他疾病共有的,这使得医生很难识别感染。为了帮助医生,设计了许多方法,使用不同的特征,如血液报告、肺和心脏特征来检测疾病。该方法利用磁共振成像扫描装置捕获肺部图像并记录心脏特征。利用图像提取肺特征,并从心脏图中提取心脏特征。同样,从血液样本中提取特征。通过从人身上提取这些特征,该方法估计不同的体重来预测疾病。不同的方法以不同的方式估计样本的相似度来对输入样本进行分类。然而,在医学领域,图像处理技术被用于解决不同的问题;同样的方法也被用于疾病的检测。此外,通过各种方法使用不同的特征集来检测Covid-19的存在。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Analysis Performance Of Image Processing Technique Its Application by Decision Support Systems On Covid-19 Disease Prediction Using Convolution Neural Network
The Covid-19 pandemic has been identified as a key issue for human society, in recent times. The presence of the infection on any human is identified according to different symptoms like cough, fever, headache, breathless and so on. However, most of the symptoms are shared by various other diseases, which makes it challenging for the medical practitioners to identify the infection. To aid the medical practitioners, there are a number of approaches designed which use different features like blood report, lung and cardiac features to detect the disease. The method captures the lung image using magnetic resonance imaging scan device and records the cardiac features. Using the image, the lung features are extracted and from the cardiac graph, the cardiac features are extracted. Similarly, from the blood samples, the features are extracted. By extracting such features from the person, the method estimates different weight measures to predict the disease. Different methods estimate the similarity of the samples in different ways to classify the input sample. However, the image processing techniques are used for different problems in medical domain; the same has been used in the detection of the disease. Also, the presence of Covid-19 is detected using different set of features by various approaches.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Taylor Sun Flower Optimization-Based Compressive Sensing for Image Compression and Recovery Special Issue on Failed Approaches and Insightful Losses in Cryptology - Foreword Role of Machine Learning on Key Extraction for Data Privacy Preservation of Health Care Sectors in IoT Environment Incorrectly Generated RSA Keys: How I Learned To Stop Worrying And Recover Lost Plaintexts Smart Multimedia Compressor - Intelligent Algorithms for Text and Image Compression
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1