[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-290456-105":59,"doc-detail-290456-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","covid-19-prediction-using-machine-learning-methods-article-review","Covid-19 Prediction using Machine Learning Methods - Article Review","","The COVID-19 pandemic has required new approaches for controlling viral spread, and machine learning (ML) offers promising support. This article review investigates recent ML algorithms for COVID-19 prediction, emphasizing how these methods may improve decision-making and optimize resource allocation during periods of highest impact. A scoping review was conducted in Google Scholar (2020–2022), selecting 20 eligible articles from 99 screened records. Results indicate ML-powered tools can reduce strain on healthcare systems by analyzing large medical datasets.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/covid-19-prediction-using-machine-learning-methods-article-review/290456/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/covid-19-prediction-using-machine-learning-methods-article-review/290456.png","ImageObject",300,407,{"name":92,"@type":93},"Hazel","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main purpose of this article review?","Question",{"text":112,"@type":113},"It explores the latest machine learning (ML) algorithms used for COVID-19 prediction and considers their potential to support better decision-making and resource allocation during peak pandemic periods.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the literature search conducted?",{"text":117,"@type":113},"A scoping review was performed using Google Scholar with the keywords “COVID-19,” “prediction,” and “machine learning,” constrained to 2020–2022.",{"name":119,"@type":110,"acceptedAnswer":120},"What types of learning approaches are discussed for ML in healthcare?",{"text":121,"@type":113},"The text classifies ML into supervised learning, unsupervised learning, and reinforcement learning, and notes its use for handling complex, heterogeneous healthcare data.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},290456,1789641729,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":129,"read_time":144,"preview_page_count":4},137441390410,"https://ap-avatar.wpscdn.com/avatar/2000252f4ab5702993?_k=1776741390130283984","Covid-19 Prediction using Machine Learning Methods: An Article Review  \nSamera Shams Hussein a, Wisal Hashim Abdulsalam b* Wisam Abed Shukurc  \na Lecturer in Computer Science Department/College of Education for Pure Science/Ibn-AlHaitham/University of Baghdad, Iraq, ORCID [https://orcid.org/0000-0002-9582-0313](https://orcid.org/0000-0002-9582-0313)[ ](https://orcid.org/0000-0002-9582-0313)[b](b Lecturer in Computer Science Department/College of Education for Pure Science/Ibn-Al-)[ Lecturer in Computer Science Department/College of Education for Pure Science/Ibn-Al-](b Lecturer in Computer Science Department/College of Education for Pure Science/Ibn-Al-)Haitham/University of Baghdad, Iraq, ORCID [https://orcid.org/0000-0003-0453-095X](https://orcid.org/0000-0003-0453-095X)  \nc Assistant Lecturer in Computer Science Department/College of Education for Pure Science/Ibn-AlHaitham/University of Baghdad, Iraq, ORCID [https://orcid.org/0000-0001-5000-5537](https://orcid.org/0000-0001-5000-5537)  \nCorresponding author:  \nE-mail: b* [wisal.h@ihcoedu.uobaghdad.edu.iq](wisal.h@ihcoedu.uobaghdad.edu.iq)  \nAbstract  \nThe COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.  \nTo conduct this scoping review, we performed a Google Scholar literature search using\"COVID-19,\" \"prediction,\" and \"machine learning\" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.  \nOur systematic literature review demonstrates that ML-powered tools can alleviate the burden on healthcare systems. These tools can analyze significant amounts of medical data and potentially improve predictive and preventive healthcare.  \nKeywords: COVID-19, Machine learning (ML), Prediction, Feature Selection, Artificial Intelligence (AI) .  \n1.Introduction  \nThe World Health Organization (WHO), declared on March 11th, 2020 the coronavirus, also known as COVID-19, a global pandemic [1] . Since then, the virus has caused widespread public health problems, costing the global economy billions of dollars in lost productivity. The existing health systems have been unable to keep up with the spread ofCOVID-19, underscoring the need for new methods of controlling pandemics. In response to this crisis, researchers around the world are leveraging science and technology, including medical image processing and ML [2] .  \nThe goal of ML, a branch of Artificial Intelligence (AI), is to develop systems that can learn from experience and advance without programming as in [3-5] . It can be classified  \ninto three categories: supervised learning, unsupervised learning, and reinforcement learning. In healthcare, ML is useful for processing complex and heterogeneous health data. It can be used in several ways, such as identifying and tracking outbreaks, diagnosing COVID-19, processing healthcare claims, and developing drugs and vaccines using supercomputers. The current study focuses on using ML to predict COVID-19, which is typically framed as a classification or regression problem. Some of the commonly used algorithms include Naive Bayes (NB), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Adaptive Boosting (AdaBoost), Gradient-boosted Decision Tree (GBDT), Extra Tree Classifier (ETC), Artificial Neural Network (ANN), Restricted Boltzmann Machine (RBM), Linear Regression (LR), Recursive Feature Elimination (RFE), and Extremely Randomized Trees (ERT) . These algorithms offer various advantages, including quick classification, precise predictions, and the ability to handle complex data [6, 7] .  \n","cbCaihw0pXJBHXrG","https://ap.wps.com/l/cbCaihw0pXJBHXrG","pdf",285603,14,"English","# Abstract\n# Keywords\n# 1. Introduction\n# 2. Methodology","[{\"question\":\"What is the main purpose of this article review?\",\"answer\":\"It explores the latest machine learning (ML) algorithms used for COVID-19 prediction and considers their potential to support better decision-making and resource allocation during peak pandemic periods.\"},{\"question\":\"How was the literature search conducted?\",\"answer\":\"A scoping review was performed using Google Scholar with the keywords “COVID-19,” “prediction,” and “machine learning,” constrained to 2020–2022.\"},{\"question\":\"What types of learning approaches are discussed for ML in healthcare?\",\"answer\":\"The text classifies ML into supervised learning, unsupervised learning, and reinforcement learning, and notes its use for handling complex, heterogeneous healthcare data.\"}]","Covid-19 Prediction using Machine Learning Methods - Article Review | PDF",35]