[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125632-en":3,"doc-seo-125632-105":30,"detail-sidebar-cat-0-en-105":91},{"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":4,"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},125632,962075006959,"Anda","https://ap-avatar.wpscdn.com/avatar/e0002397efbe92a78e?_k=1776741047341049297",7,"Healthcare","Comprehensive study - machine learning approaches for COVID-19 diagnosis","COVID-19 spreads rapidly worldwide and creates urgent pressure for early detection and real-time monitoring solutions. The work surveys recent artificial intelligence and Internet of Things (IoT) based approaches and aims to provide researchers with a comprehensive summary of AI/IoT/cloud/fog methods, algorithms, datasets and sources, as well as proposed models, frameworks, devices, and monitoring systems, organized for pandemic control. It also introduces an IoT-sensor vision validated with a 1 million-patient dataset.","International Journal of Electrical and Computer Engineering (IJECE)  \nVol. 13, No. 5, October 2023, pp. 5681~5695  \nISSN: 2088-8708, DOI: 10. 11591/ijece.v13i5 .pp5681-5695 􀂈 5681  \n\n| Comprehensive study: machine learning approaches for\u003Cbr>COVID-19 diagnosis\u003Cbr>Amir Nasir Hussein1, Seyed Vahab Al-Din Makki1, Ali Al-Sabbagh2,3\u003Cbr>1Department of Electrical Engineering, Faculty of Engineering, Razi University, Kermanshah, Iran 2Computer Engineering Techniques department, Al Taff University College, Karbala, Iraq 3Ministry of Communication, Informatics Telecommunications and Public Company, Karbala, Iraq |  |\n| --- | --- |\n| Article Info\u003Cbr>Article history:\u003Cbr>Received Dec 30, 2022 Revised Mar 19, 2023 Accepted Mar 28, 2023\u003Cbr>Keywords:\u003Cbr>Coronavirus disease 2019 Intelligent framework Internet of things Machine learning Smart detection\u003Cbr>Corresponding Author: | Coronavirus disease 2019 (COVID-19) is caused a large number of death since has declared as an international pandemic in December 2019, and it is spreading all over the world (more than 200 countries) . This situation puts the health organizations in an aberrant demand for urgent needs to develop significant early detection and monitoring smart solutions. Therefore, that new system or solution might be capable to identify COVID-19 quickly and accurately. Nowadays, the science of artificial intelligence (AI), and internet of things (IoT) techniques have an extensive range of applications, it can be initiated a possible solution for early detection and accurate decisions. We believe, combine both of the IoT revolution and machine learning (ML) methods are expected to reshape healthcare treatment strategies to provide smart (diagnosis, treatments, monitoring, and hospitals) . This work aims to overview the recent solutions that have been used for early detection, and to provide the researchers a comprehensive summary that contribute to the pandemic control such AI, IoT, cloud, fog, algorithms, and all the dataset and their sources that recently published. In addition, all models, frameworks, monitoring systems, devices, and ideas (in four sections) have been sufficiently presented with all clarifications and justifications. Also, we propose a new vision for early detection based on IoT sensors data entry using 1 million patients-data to verify three proposed methods.\u003Cbr>This is an open access article under the CC BY-SA license.\u003Cbr>\u003Cbr>ABSTRACT |\n| Seyed Vahab Al-Din Makki\u003Cbr>Department of Electrical Engineering, Faculty of Engineering, Razi University Kermanshah, Iran\u003Cbr>[Email: v.makki@razi.ac.ir](Email: v.makki@razi.ac.ir) |  |\n\n1. INTRODUCTION  \nCoronavirus disease 2019 (COVID-19) is caused by a highly contagious novel virus and was first discovered in Wuhan City in Hubei, China, where the pandemic initially began. The pandemic quickly spread across China and then the entire world. COVID-19 was declared by the World Health Organization (WHO) on March 11, 2020, as a pandemic that causes people to suffer acute respiratory infection and the new virus is caused by the severe acute respiratory syndrome (SARS) covid 2 virus [1], [2] . There are general indications of the disease, including headache, dry cough, difficulty breathing, decreased smell and taste, and weakness, although the coronavirus affects all age groups, the most vulnerable group to infection are those over 30 years old, and the elderly. The symptoms are more severe and can spread among young people and children early detection of infected people is one of the most important steps in combating the virus [3]–[7] . This work aims to overview the recent solutions that have been used for early detection, and to provide the researchers a comprehensive summary that contribute to the pandemic control such artificial intelligent (AI),  \ninternet of things (IoT), cloud, fog, algorithms. The main gab is can be summarized as: first, the methods of machine learning (ML) that have been used, second: the reliable datasets, ","cbCaifVRInLS0APU","https://ap.wps.com/l/cbCaifVRInLS0APU","pdf",443276,1,15,"English","en",105,"# Introduction\n## COVID-19 background and need for early detection\n## AI and IoT approaches for diagnosis and monitoring\n## Motivation and research focus","[{\"question\":\"Why is early detection of COVID-19 considered critical in this work?\",\"answer\":\"Early detection helps counter the spread of a highly contagious virus and supports timely diagnosis and monitoring. The document links vulnerable groups and symptom progression to the need for urgent detection solutions.\"},{\"question\":\"What technologies and components does the survey emphasize?\",\"answer\":\"The survey highlights artificial intelligence and Internet of Things techniques, along with cloud and fog, algorithms, datasets, and their sources. It also covers proposed models, monitoring systems, devices, and ideas.\"},{\"question\":\"What is the paper’s proposed validation idea for early detection?\",\"answer\":\"The paper proposes an IoT-sensor based vision for early detection and indicates verification of three proposed methods using 1 million patients-data.\"}]","Comprehensive study - machine learning approaches for COVID-19 diagnosis | PDF",1785900319,38,{"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":86,"head_meta":88,"extra_data":90,"updated_unix":28},"comprehensive-study-machine-learning-approaches-for-covid-19-diagnosis","",{"@graph":36,"@context":85},[37,54,68],{"@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/healthcare/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/comprehensive-study-machine-learning-approaches-for-covid-19-diagnosis/125632/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is early detection of COVID-19 considered critical in this work?","Question",{"text":75,"@type":76},"Early detection helps counter the spread of a highly contagious virus and supports timely diagnosis and monitoring. The document links vulnerable groups and symptom progression to the need for urgent detection solutions.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What technologies and components does the survey emphasize?",{"text":80,"@type":76},"The survey highlights artificial intelligence and Internet of Things techniques, along with cloud and fog, algorithms, datasets, and their sources. 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