[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124312-en":3,"doc-seo-124312-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124312,962075114765,"Quinn","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","COVID-19 detection using machine learning and fusion-based deep learning models - Abstract","COVID-19 detection using machine learning and fusion-based deep learning models addresses the urgent need for faster and more reliable identification of COVID-19 cases. The approach proposes machine learning and deep learning systems that estimate the probability of COVID-19 presence from CT images. In the ML pipeline, CT images are segmented to extract lung ROI, then Gabor-Wavelet features and deep-based features are used to train and evaluate an SVM classifier. In the DL pipeline, CT images are fed directly into CNN, GoogleNet, and ResNet50, and fusion strategies combine both SVM feature sets and deep models to improve performance, reaching peak accuracy, precision, and recall around 96.4%, 96.2%, and 96.2%.","| \u003Cbr>\u003Cbr>Wasit Journal of Engineering Sciences\u003Cbr>Journal homepage: [https://ejuow.uowasit.edu.iq](https://ejuow.uowasit.edu.iq) |  |\n| --- | --- |\n| COVID-19 detection using machine learning and fusion-based\u003Cbr>deep learning models\u003Cbr>Fatima Raheem Sultan1, Manaf K. Hussein2 |  |\n\nAffiliations  \n1Department of Electrical Engineering College of Engineering  \nUniversity of Wasit Wasit, Iraq  \nCorrespondence  \n2Department of Electrical Engineering. University of Wasit,  \nKut, Iraq.  \nEmail:  \n[fatimar302@uowasit.edu.iq](fatimar302@uowasit.edu.iq)  \nReceived  \n28-February-2023  \nRevised  \n13-May-2023  \nAccepted  \n11-July-2023  \nDoi: 10.31185/ejuow.Vol11.Iss2.439  \nAbstract:  \nThe COVID-19 pandemic has been one of the most challenging crises attacking the world in the last three years. Many systems have been introduced in the field ofCOVID-19 detection.  \nIn this research, machine learning (ML) and deep learning (DL) models for the detection ofCOVID-19 with a probability of the presence ofCOVID-19 are proposed. In the machine learning scenario, the COVID-19 dataset is split into 70% training and 30% testing, and a segmentation process is applied to the CT images in order to get the lung ROI only. The features of CT images are then extracted using Gabor-Wavelet and deep-based features. The SVM classifier is then trained and evaluated. For the deep learning model, the CT images are fed into the model without feature extraction, and three different DL models (CNN, GoogleNet, and ResNet50) are trained and evaluated. Other scenarios are proposed in which the SVM Gabor-Wavelet and deep features are fused, and the three deep learning models are also fused to get better performance. The experiments show that the best model is the deep-based fusion model by which the system achieved 96.4156%, 96.1905%, and 96.1905% for accuracy, precision, and recall, respectively.  \nKeywords: Machine Learning, Deep Learning, SVM, COVID-19, Model Fusion.  \nالخلاصة: كانت جائحة COVID19- واحدة من أكثر الأزمات تحديًا التي هزت العالم في السنوات الثلاث الماضية. تم تقديم العديد من الأنظمة فيمجال الكشف عن COVID19- .  \nفي هذا البحث، تم اقتراح نماذج التعلم الآلي والتعلم العميق للكشف عن COVID19- مع إعطاء نسب لاحتمال وجود COVID19-. في سيناريوالتعلم الآلي، يتم تقسيم مجموعة بيانات COVID19- إلى ٪70 تدريب و٪30 اختبار، ويتم تطبيق عملية تجزئة على صور التصوير المقطعي المحوسبمن أجل الحصول على منطقة الرئة فقط. ثم يتم استخراج ميزات صور التصوير المقطعي المحوسب باستخدام Wavelet-Gabor والميزات العميقة. ثم يتمتدريب مصنف SVM وتقييمه. بالنسبة لنموذج التعلم العميق، يتم إدخال صور التصوير المقطعي المحوسب في النموذج دون استخراج الميزات، ويتم تدريبوتقييم ثلاثة نماذج مختلفة للتعلم العميق هي (CNN, GoogleNet, ResNet) . تم اقتراح سيناريوهات أخرى يتم فيها دمج Wavelet-SVM Gabor والميزات العميقة، كما يتم دمج نماذج التعلم العميق الثلاثة أيضًا للحصول على أداء أفضل. أظهرت التجارب أن أفضل نموذج هو نموذج الدمج لأنظمة التعلمالعميق الذي حقق النظام بواسطته ٪96.4156 و٪96.1905 و٪96.1905 للدقة والدقة والاسترجاع على التوالي.  \n1. INTRODUCTION  \nOne of the most important challenges over the past three years was the COVID-19 pandemic. This disease has caused the infection and death of millions of people. The laboratory test polymerase chain reaction (PCR), which is carried out on samples collected from the patient's nose or throat, is now used to identify COVID-19. Results from this PCR test take about a day to be obtained [1] . The high rate of false negatives (those who have COVID-19 but the test says they don't) is one of PCR's numerous drawbacks. PCR tests have a specificity and sensitivity range of 37% to 71% .  \n[2] . On the other hand, because the outcome can be determined a few minutes after the imaging session, computed tomography (CT) and x-ray imaging have become quite fashionable in the diagnosis of COVID-19. In addition, the doctor can see more details about the disease's stage and progression. The COVID-2019 epidemic has put the entire world under a state of containment in an effort to stop fur","cbCaievAN3hGg3sy","https://ap.wps.com/l/cbCaievAN3hGg3sy","pdf",1197427,1,12,"English","en",105,"# Abstract\n# Introduction\n## COVID-19 diagnostic challenges\n## CT and X-ray imaging for diagnosis\n## Prior work using ML and DL models\n## Fusion-based approaches","[{\"question\":\"What data and preprocessing steps are used in the machine learning approach?\",\"answer\":\"The COVID-19 dataset is split into 70% training and 30% testing, and CT images are segmented to obtain only the lung region of interest (ROI).\"},{\"question\":\"How are features extracted and classified in the machine learning pipeline?\",\"answer\":\"CT features are extracted using Gabor-Wavelet and deep-based features, and an SVM classifier is trained and evaluated using these features.\"},{\"question\":\"Which deep learning models are trained, and how does fusion improve results?\",\"answer\":\"CNN, GoogleNet, and ResNet50 are trained on CT images without manual feature extraction. Fusion combines SVM-based Gabor-Wavelet/deep features and also combines the outputs of the three deep learning models to improve performance.\"}]","COVID-19 detection using machine learning and fusion-based deep learning models - Abstract | PDF",1785821537,30,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"covid-19-detection-using-machine-learning-and-fusion-based-deep-learning-models-abstract","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/covid-19-detection-using-machine-learning-and-fusion-based-deep-learning-models-abstract/124312/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05","2026-08-04",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What data and preprocessing steps are used in the machine learning approach?","Question",{"text":76,"@type":77},"The COVID-19 dataset is split into 70% training and 30% testing, and CT images are segmented to obtain only the lung region of interest (ROI).","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How are features extracted and classified in the machine learning pipeline?",{"text":81,"@type":77},"CT features are extracted using Gabor-Wavelet and deep-based features, and an SVM classifier is trained and evaluated using these features.",{"name":83,"@type":74,"acceptedAnswer":84},"Which deep learning models are trained, and how does fusion improve results?",{"text":85,"@type":77},"CNN, GoogleNet, and ResNet50 are trained on CT images without manual feature extraction. Fusion combines SVM-based Gabor-Wavelet/deep features and also combines the outputs of the three deep learning models to improve performance.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":29,"slug":122},"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":107,"slug":138},19,"General","general"]