[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125948-en":3,"doc-seo-125948-105":31,"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":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},125948,137451207643,"Noah","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",7,"Healthcare","Accurate COVID-19 detection using full blood count data and machine learning","COVID-19 has spread rapidly worldwide, making accurate diagnosis central to effective pandemic control. Existing RT-PCR testing is sensitive but time-consuming and depends on expensive equipment and limited test kits, while antigen lateral flow tests have lower sensitivity and are less suitable early in outbreaks. This study applies traditional machine learning and convolutional neural networks to hematology analyzer full blood count data, demonstrating COVID-19 detection accuracy above 97%. Classifier performance is compared to support use in current and future pandemics.","Int. J. Metrol. Qual. Eng. 15, 17 (2024)  \n© R. Yang et al., Published by EDP Sciences, 2024 [https://doi.org/10.1051/ijmqe/2024013](https://doi.org/10.1051/ijmqe/2024013)  \nInternational Journal of Metrology and Quality Engineering  \nAvailable online at:  \n[www.metrology-journal.org](www.metrology-journal.org)  \n\n| RESEARCH ARTICLE   |  |\n| --- | --- |\n\nAccurate COVID-19 detection using full blood count data and machine learning  \nRichard Yang1 , Ding Chen2 , Qingping Yang1,* , Yang Qiu2 , and Fang Wang1  \n1 College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, UK  \n2 Wuhan Union Hospital Affiliated with Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China  \nReceived: 17 August 2023 / Accepted: 25 June 2024  \nAbstract. COVID-19 has spread rapidly worldwide in the past three years, triggering partial and full lockdowns globally. The successful control of the COVID-19 pandemic on a global scale depended heavily upon the accurate detection ofCOVID-19. However, the main diagnostic tests for COVID-19 have some significant limitations, e.g.  \nthe major nucleic acid (RT-PCR) tests while having a high sensitivity are time-consuming and require expensive equipment with the shortage of test kits in many countries. Antigen lateral flow tests have a lower sensitivity and they cannot be used during the early pandemic as well as usually more expensive than the full or complete blood count test used in this paper which can be potentially performed using a finger blood sample. The last decade has seen rapid growth of AI, particularly deep learning, which has found wide applications in medical image analysis, with results comparable to and even surpassing human expert performance. There have been several machine learning models reported for COVID-19 diagnostics or prognosis predictions, most of them based on CT and X-ray images. In this paper we have applied traditional machine learning and convolutional neural networks (CNNs) based deep learning to the blood test data obtained from hematology analyzers and demonstrated that the AI models can be used to detect COVID-19 with a high degree of accuracy (>97%) . The performance of different classifiers will be compared and discussed. The work should have potential applications in current COVID-19 and future pandemics.  \nKeywords: COVID-19 / full blood count / machine learning / deep learning / convolutional neural networks  \n1 Introduction  \nCOVID-19 was initially reported in Wuhan, China, then quickly spread worldwide and was declared a global pandemic by the World Health Organization (WHO) on the 11th of March 2020 . It is a type of SARS-CoV2 virus that produces various symptoms (e.g. acute respiratory failure, acute respiratory distress syndrome (ARDS), and COVID-19 pneumonia) in humans that can cause death. This has led many countries to enforce strict procedures such as lockdowns and the closure of borders, schools, and other sectors.  \nThe successful control of the pandemic is heavily dependentonthe accurate detectionofCOVID-19. However, the accurate detection of the virus is a challenging task, with current methods of testing having significant limitations, e.g. major nucleic acid (RT-PCR) tests while having a high sensitivity (>90%) [1] are time-consuming  \n*Corresponding author: [qingping.yang@brunel.ac.uk](qingping.yang@brunel.ac.uk)  \nand require expensive equipment with the shortage of test kitsin many countries as well. Antigen lateralflow tests have a lower sensitivity [2] and they cannot be used during the early pandemic aswell as usually more expensivethan the full blood count test used in this paper which can be potentially performed using a finger blood sample.  \nMachine learning can provide very powerful methods to detect COVID-19 [3] . In general, there are many different machine learning methods that can be used for the detection of COVID-19 such as Logistic Regression, Naive Bayes, k-nearest neighbours (KNN), Supp","cbCairOjX5HPr06a","https://ap.wps.com/l/cbCairOjX5HPr06a","pdf",1659206,4,1,9,"English","en",105,"# Introduction\n## COVID-19 impact and the need for accurate detection\n## Limitations of RT-PCR and antigen tests\n## Machine learning approaches for COVID-19 detection\n# Methods\n## Data from hematology analyzers and model types\n## Comparison of classifiers and CNN-based deep learning\n# Results and Discussion\n## Detection accuracy and classifier performance comparison\n# Conclusion\n## Potential applications for current and future pandemics","[{\"question\":\"Why is COVID-19 detection challenging with existing tests like RT-PCR and antigen lateral flow?\",\"answer\":\"RT-PCR, while highly sensitive, is time-consuming and requires expensive equipment and test kits. Antigen lateral flow tests have lower sensitivity and are less suitable during early outbreak stages.\"},{\"question\":\"What input data does the study use for COVID-19 detection?\",\"answer\":\"The models use full blood count data obtained from hematology analyzers, which can be collected from finger blood samples.\"},{\"question\":\"How accurate are the proposed machine learning and CNN-based models?\",\"answer\":\"The paper reports COVID-19 detection with a high degree of accuracy, exceeding 97%, and compares performance across different classifiers.\"}]","Accurate COVID-19 detection using full blood count data and machine learning | PDF",1785902182,23,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"accurate-covid-19-detection-using-full-blood-count-data-and-machine-learning","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/healthcare/",3,{"item":53,"name":13,"@type":44,"position":20},"https://docshare.wps.com/document/accurate-covid-19-detection-using-full-blood-count-data-and-machine-learning/125948/",{"url":53,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-23","2026-08-05",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},"Why is COVID-19 detection challenging with existing tests like RT-PCR and antigen lateral flow?","Question",{"text":76,"@type":77},"RT-PCR, while highly sensitive, is time-consuming and requires expensive equipment and test kits. Antigen lateral flow tests have lower sensitivity and are less suitable during early outbreak stages.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What input data does the study use for COVID-19 detection?",{"text":81,"@type":77},"The models use full blood count data obtained from hematology analyzers, which can be collected from finger blood samples.",{"name":83,"@type":74,"acceptedAnswer":84},"How accurate are the proposed machine learning and CNN-based models?",{"text":85,"@type":77},"The paper reports COVID-19 detection with a high degree of accuracy, exceeding 97%, and compares performance across different classifiers.","https://schema.org",{"og:url":53,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,119,124,128,131,135],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":117,"slug":118},40,"healthcare",{"id":120,"doc_module":4,"doc_module_name":47,"category_name":121,"show_sort_weight":122,"slug":123},8,"Research & Report",30,"research-report",{"id":22,"doc_module":4,"doc_module_name":47,"category_name":125,"show_sort_weight":126,"slug":127},"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":47,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":47,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":47,"category_name":137,"show_sort_weight":107,"slug":138},19,"General","general"]