مدل بندی و داده کاوی داده های جهانی بیماران ویروس کووید ۱.
Introduction: Data mining techniques, including decision tree algorithms can be used for modeling and identifying those at risk of developing COVID-19. The main goal of this study is estimating the risk of death of patients due to COVID-19, using the classification and regression tree (CART) algorit...
| Publicado en: | Iranian Journal of Emergency Medicine / Ṭibb-i Urzhāns-i Īrān Vol. 7; pp. 1 - 7 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Shahid Beheshti University of Medical Sciences
2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=150028721&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 150028721 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23833645 HOTA jtl: Iranian Journal of Emergency Medicine / Ṭibb-i Urzhāns-i Īrān issn: 23833645 maglogo: N pubinfo: dt: 2020 vid: 7 pid: 87963 pub: Shahid Beheshti University of Medical Sciences artinfo: ui: 150028721 150028721 ppf: 1 ppct: 6 formats: tig: atl: مدل بندی و داده کاوی داده های جهانی بیماران ویروس کووید ۱. aug: au: مصطفی بسکابادی مهدی دوست پرست affil: دانشگاه علوم پزشکی مشهد، مشهد، ایران. sug: ab: Introduction: Data mining techniques, including decision tree algorithms can be used for modeling and identifying those at risk of developing COVID-19. The main goal of this study is estimating the risk of death of patients due to COVID-19, using the classification and regression tree (CART) algorithm based on the observed effective factors. Methods: This paper is an analytical study and the data of all patients with COVID-19 registered on the Kaggle site through Johns Hopkins University, was extracted. There was a total of 26,031 records from various countries. Data analysis was performed using JMP statistical software version 13. In the modeling section, decision tree algorithm and CART model were used. Results: The results of the classification and regression tree showed that among quantitative variables, age, the interval between hospitalization and result, the interval between onset of symptoms and test result, and the interval between hospitalization and test result, and the qualitative variable of gender were the most important factors affecting the outcome of patient treatment, respectively. According to the analysis of words, fever, cough, sore throat, fatigue, weakness, headache, chills, and runny nose, respectively, were the most common symptoms among patients with this disease. Conclusion: The accuracy of the fitted model was shown to be 94.1% for experimental data and 91.1% for educational data using the area under the receiver operating characteristic (ROC) curve. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: Arabic refInfo: holdings: @attributes: islocal: N |
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