Cargando…
Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models
| Autores principales: | , , , , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
JMIR Publications
2020
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7539158/ https://www.ncbi.nlm.nih.gov/pubmed/32960774 http://dx.doi.org/10.2196/23996 |
| _version_ | 1783591007314509824 |
|---|---|
| author | Liu, Dianbo Clemente, Leonardo Poirier, Canelle Ding, Xiyu Chinazzi, Matteo Davis, Jessica Vespignani, Alessandro Santillana, Mauricio |
| author_facet | Liu, Dianbo Clemente, Leonardo Poirier, Canelle Ding, Xiyu Chinazzi, Matteo Davis, Jessica Vespignani, Alessandro Santillana, Mauricio |
| author_sort | Liu, Dianbo |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-7539158 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2020 |
| publisher | JMIR Publications |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-75391582020-10-20 Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models Liu, Dianbo Clemente, Leonardo Poirier, Canelle Ding, Xiyu Chinazzi, Matteo Davis, Jessica Vespignani, Alessandro Santillana, Mauricio J Med Internet Res Corrigenda and Addenda JMIR Publications 2020-09-22 /pmc/articles/PMC7539158/ /pubmed/32960774 http://dx.doi.org/10.2196/23996 Text en ©Dianbo Liu, Leonardo Clemente, Canelle Poirier, Xiyu Ding, Matteo Chinazzi, Jessica Davis, Alessandro Vespignani, Mauricio Santillana. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.09.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
| spellingShingle | Corrigenda and Addenda Liu, Dianbo Clemente, Leonardo Poirier, Canelle Ding, Xiyu Chinazzi, Matteo Davis, Jessica Vespignani, Alessandro Santillana, Mauricio Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models |
| title | Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models |
| title_full | Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models |
| title_fullStr | Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models |
| title_full_unstemmed | Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models |
| title_short | Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models |
| title_sort | correction: real-time forecasting of the covid-19 outbreak in chinese provinces: machine learning approach using novel digital data and estimates from mechanistic models |
| topic | Corrigenda and Addenda |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7539158/ https://www.ncbi.nlm.nih.gov/pubmed/32960774 http://dx.doi.org/10.2196/23996 |
| work_keys_str_mv | AT liudianbo correctionrealtimeforecastingofthecovid19outbreakinchineseprovincesmachinelearningapproachusingnoveldigitaldataandestimatesfrommechanisticmodels AT clementeleonardo correctionrealtimeforecastingofthecovid19outbreakinchineseprovincesmachinelearningapproachusingnoveldigitaldataandestimatesfrommechanisticmodels AT poiriercanelle correctionrealtimeforecastingofthecovid19outbreakinchineseprovincesmachinelearningapproachusingnoveldigitaldataandestimatesfrommechanisticmodels AT dingxiyu correctionrealtimeforecastingofthecovid19outbreakinchineseprovincesmachinelearningapproachusingnoveldigitaldataandestimatesfrommechanisticmodels AT chinazzimatteo correctionrealtimeforecastingofthecovid19outbreakinchineseprovincesmachinelearningapproachusingnoveldigitaldataandestimatesfrommechanisticmodels AT davisjessica correctionrealtimeforecastingofthecovid19outbreakinchineseprovincesmachinelearningapproachusingnoveldigitaldataandestimatesfrommechanisticmodels AT vespignanialessandro correctionrealtimeforecastingofthecovid19outbreakinchineseprovincesmachinelearningapproachusingnoveldigitaldataandestimatesfrommechanisticmodels AT santillanamauricio correctionrealtimeforecastingofthecovid19outbreakinchineseprovincesmachinelearningapproachusingnoveldigitaldataandestimatesfrommechanisticmodels |