{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T05:11:21Z","timestamp":1777957881280,"version":"3.51.4"},"reference-count":20,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T00:00:00Z","timestamp":1618790400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100011821","name":"Ministry of Education \u2013 Kingdom of Saudi Arabi","doi-asserted-by":"publisher","award":["Covid19-2020-059-CSIT"],"award-info":[{"award-number":["Covid19-2020-059-CSIT"]}],"id":[{"id":"10.13039\/501100011821","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Scientific Programming"],"published-print":{"date-parts":[[2021,4,19]]},"abstract":"<jats:p>The novel coronavirus (COVID-19) outbreak produced devastating effects on the global economy and the health of entire communities. Although the COVID-19 survival rate is high, the number of severe cases that result in death is increasing daily. A timely prediction of at-risk patients of COVID-19 with precautionary measures is expected to increase the survival rate of patients and reduce the fatality rate. This research provides a prediction method for the early identification of COVID-19 patient\u2019s outcome based on patients\u2019 characteristics monitored at home, while in quarantine. The study was performed using 287 COVID-19 samples of patients from the King Fahad University Hospital, Saudi Arabia. The data were analyzed using three classification algorithms, namely, logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB). Initially, the data were preprocessed using several preprocessing techniques. Furthermore, 10-k cross-validation was applied for data partitioning and SMOTE for alleviating the data imbalance. Experiments were performed using twenty clinical features, identified as significant for predicting the survival versus the deceased COVID-19 patients. The results showed that RF outperformed the other classifiers with an accuracy of 0.95 and area under curve (AUC) of 0.99. The proposed model can assist the decision-making and health care professional by early identification of at-risk COVID-19 patients effectively.<\/jats:p>","DOI":"10.1155\/2021\/5587188","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T03:19:57Z","timestamp":1618975197000},"page":"1-10","source":"Crossref","is-referenced-by-count":50,"title":["Machine Learning-Based Model to Predict the Disease Severity and Outcome in COVID-19 Patients"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8246-4658","authenticated-orcid":true,"given":"Sumayh S.","family":"Aljameel","sequence":"first","affiliation":[{"name":"College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Irfan Ullah","family":"Khan","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nida","family":"Aslam","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Malak","family":"Aljabri","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eman S.","family":"Alsulmi","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1"},{"key":"2"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2020.110137"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-020-01582-x"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2021.014042"},{"key":"6","first-page":"1","article-title":"Anxious depression prediction in real-time social data","author":"A. Kumar"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2020.110059"},{"key":"8","article-title":"An early warning tool for predicting mortality risk of COVID-19 patients using machine learning","author":"M. E. H. Chowdhury","year":"2020"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patter.2020.100074"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1101\/2020.02.27.20028027"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1101\/2020.09.18.20197319"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcv.2020.104431"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.3389\/fcell.2020.00683"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyaa171"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0243262"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17228386"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-75767-2"},{"key":"18","doi-asserted-by":"crossref","DOI":"10.1002\/9781118548387","volume-title":"Applied Logistic Regression","author":"R. X. S. D. W. Hosmer","year":"2013"},{"key":"19","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4419-9326-7","volume-title":"Ensemble Machine Learning","author":"Y. M. C. Zhang","year":"2012"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"}],"container-title":["Scientific Programming"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/sp\/2021\/5587188.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/sp\/2021\/5587188.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/sp\/2021\/5587188.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T03:20:00Z","timestamp":1618975200000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/sp\/2021\/5587188\/"}},"subtitle":[],"editor":[{"given":"Shah","family":"Nazir","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2021,4,19]]},"references-count":20,"alternative-id":["5587188","5587188"],"URL":"https:\/\/doi.org\/10.1155\/2021\/5587188","relation":{},"ISSN":["1875-919X","1058-9244"],"issn-type":[{"value":"1875-919X","type":"electronic"},{"value":"1058-9244","type":"print"}],"subject":[],"published":{"date-parts":[[2021,4,19]]}}}