Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Shimon Sheiba"'
Autor:
Noam Barda, Dan Riesel, Amichay Akriv, Joseph Levy, Uriah Finkel, Gal Yona, Daniel Greenfeld, Shimon Sheiba, Jonathan Somer, Eitan Bachmat, Guy N. Rothblum, Uri Shalit, Doron Netzer, Ran Balicer, Noa Dagan
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Identification of individuals at risk of severe COVID-19 disease could inform treatment and public health planning. Here, the authors develop and validate a risk prediction model for COVID-19 mortality in Israel by building a model for severe respira
Externí odkaz:
https://doaj.org/article/b6f41c67d1bb44c58e4540ffa24f6729
Autor:
Shimon Sheiba, Jonathan Somer, Gal Yona, Guy N. Rothblum, Noa Dagan, Daniel Greenfeld, Uri Shalit, Amichay Akriv, Dan Riesel, Joseph Levy, Uriah Finkel, Doron Netzer, Noam Barda, Ran D. Balicer, Eitan Bachmat
Publikováno v:
Nature Communications
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
At the COVID-19 pandemic onset, when individual-level data of COVID-19 patients were not yet available, there was already a need for risk predictors to support prevention and treatment decisions. Here, we report a hybrid strategy to create such a pre
Autor:
Dan Riesel, Daniel Greenfeld, Shimon Sheiba, Jonathan Somer, Uri Shalit, Amichay Akriv, Gal Yona, Doron Netzer, Joseph Levi, Noa Dagan, Eitan Bachmat, Ran D. Balicer, Noam Barda, Guy N. Rothblum, Uriah Finkel
With the global coronavirus disease 2019 (COVID-19) pandemic, there is an urgent need for risk stratification tools to support prevention and treatment decisions. The Centers for Disease Control and Prevention (CDC) listed several criteria that defin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0078caf1634dbe880843e615bdc001fc
https://doi.org/10.1101/2020.04.23.20076976
https://doi.org/10.1101/2020.04.23.20076976