چاپ صفحه |  صفحه نخست سامانه |  نویسندگان |  اطلاعات تفضیلی |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده ثبت کننده مقاله | عطاالله جدیری شیخ زاده |
| مرحله جاری مقاله | تایید نهایی |
| دانشکده/مرکز مربوطه | دانشکده علوم نوین پزشکی |
| کد مقاله | 84228 |
| عنوان فارسی مقاله | تحلیل توزیع کووید-۱۹ در کشورها با استفاده از یادگیری بدون نظارت |
| عنوان لاتین مقاله | Analysis of COVID-19 Distribution in Countries Using Unsupervised Machine Learning |
| نوع ارائه | سخنرانی |
| عنوان کنگره / همایش | Innovative Technologies in Engineering, Sciences and Technology |
| نوع کنگره / همایش | بین المللی |
| کشور محل برگزاری کنگره/ همایش | Iran (Islamic Republic) |
| شهر محل برگزاری کنگره/ همایش | Tehran |
| سال انتشار/ ارائه شمسی | 1402 |
| سال انتشار/ارائه میلادی | 2023 |
| تاریخ شمسی شروع و خاتمه کنگره/همایش | 1402/04/05 الی 1402/04/05 |
| آدرس لینک مقاله/ همایش در شبکه اینترنت | https://civilica.com/doc/1701718/ |
| آدرس علمی (Affiliation) نویسنده متقاضی | Department of Biomedical Engineering, Tabriz University of Medical Sciences Tabriz, Iran |
| نویسنده | نفر چندم مقاله |
|---|---|
| نسترن خاکستری | اول |
| ریحانه افغان | دوم |
| عطاالله جدیری شیخ زاده | سوم |
| عنوان | متن |
|---|---|
| کلمات کلیدی | COVID-19, Clustering methods, Unsupervised learning, K-Means, Hierarchical clustering |
| خلاصه مقاله | Although more than two years have passed since the spearing of COVID-19, a global pandemic, there are still major peaks in the number of confirmed cases and deaths. Although governments are trying to overcome this disease with different policies, it is not entirely controlled yet. In this study, two methods of unsupervised learning, K-Means and Hierarchical algorithms, were used to cluster 207 countries based on social, economic, and health characteristics. Thus, countries with similar factors can take proactive steps to control the pandemic. The optimal number of clusters was considered k=6 based on the elbow method. To obtain the most associated features, the correlation between selected variables and confirmed COVID-19 cases, deaths, and vaccination rates was analysed. The government stringency index showed a strong correlation with the number of vaccinations, whereas environmental health indicators were weakly correlated with mortality from COVID-19. Politicians can make better decisions by considering these indicators and therefore, manage the negative consequences of COVID-19. |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| TETSCONF12_011.pdf | 1402/12/22 | 744205 | دانلود |
| Certificate.pdf | 1402/12/22 | 427245 | دانلود |
