Deliverables Documents, reports (8) Governance report Report specifying decisionmaking processes and appointed members on projectinternal bodies and team as well as signed charters for all external monitoring boards and committees Assessment plan Guidelines on ethical, social, legal and psychological aspects of ENVISION Analysis of legal social and psychological aspects related to the project Outreach plan Outreach plan defining strategy tools channels dissemination and communication activities Sandman.ICU user guide and training material SandmanICU user guide and training material eLearning materials eLearning materials developed specifically for health care professionals Health economic model Health economic model including report and webtool for countryor region specific estimates Final event Final event to present the results and outcomes in the European Parliament Websites, patent fillings, videos etc. (1) ENVISION website ENVISION website with dedicated areas for different stakeholder groups Publications Peer reviewed articles (3) Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort Author(s): Harry Magunia, Simone Lederer, Raphael Verbuecheln, Bryant Joseph Gilot, Michael Koeppen, Helene A. Haeberle, Valbona Mirakaj, Pascal Hofmann, Gernot Marx, Johannes Bickenbach, Boris Nohe, Michael Lay, Claudia Spies, Andreas Edel, Fridtjof Schiefenhövel, Tim Rahmel, Christian Putensen, Timur Sellmann, Thea Koch, Timo Brandenburger, Detlef Kindgen-Milles, Thorsten Brenner, Marc Berger, Kai Zacharo Published in: Critical Care, Issue 295 (2021), 2021, Page(s) 25, ISSN 1364-8535 Publisher: BMC DOI: 10.1186/s13054-021-03720-4 ENVISION – Improve intensive care of COVID-19 patients with artificial intelligence Author(s): Alpo Olavi Värri, Antti Kallonen, Hannu Nieminen, Mark Van Gils Published in: Finnish Journal of EHealth and EWelfare, Issue 13 (4), 2021, Page(s) 449-453, ISSN 1798-0798 Publisher: Finnish Social and Health Informatics Association DOI: 10.23996/fjhw.109929 Additional file 1 of Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort Author(s): Magunia, Harry; Lederer, Simone; Verbuecheln, Raphael; Gilot, Bryant Joseph; Koeppen, Michael; Haeberle, Helene A.; Mirakaj, Valbona; Hofmann, Pascal; Marx, Gernot; Bickenbach, Johannes; Nohe, Boris; Lay, Michael; Spies, Claudia; Edel, Andreas; Schiefenhövel, Fridtjof; Rahmel, Tim; Putensen, Christian; Sellmann, Timur; Koch, Thea; Brandenburger, Timo; Kindgen-Milles, Detlef; Brenner, Thorsten; Be Published in: Springer Nature, 2021, ISSN 1364-8535 Publisher: BMC DOI: 10.6084/m9.figshare.15184814 Searching for OpenAIRE data... There was an error trying to search data from OpenAIRE No results available
