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Prediction of COVID-19 spreading profiles in South Korea, Italy and Iran by data-driven coding
This work applies a data-driven coding method for prediction of the COVID-19 spreading profile in any given population that shows an initial phase of epidemic progression. Based on the historical data collected for COVID-19 spreading in 367 cities in China and the set of parameters of the augmented...
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| Опубликовано в: : | PLoS One |
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| Главные авторы: | , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Public Library of Science
2020
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7337285/ https://ncbi.nlm.nih.gov/pubmed/32628673 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0234763 |
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