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CORDIS - EU research results
CORDIS

Intelligent plug-and-play digital tool for real-time surveillance of COVID-19 patients and smart decision-making in Intensive Care Units

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Governance report (opens in new window)

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 (opens in new window)
Guidelines on ethical, social, legal and psychological aspects of ENVISION (opens in new window)

Analysis of legal social and psychological aspects related to the project

Outreach plan (opens in new window)

Outreach plan defining strategy tools channels dissemination and communication activities

Final implementation report (opens in new window)
Sandman.ICU user guide and training material (opens in new window)

SandmanICU user guide and training material

eLearning materials (opens in new window)

eLearning materials developed specifically for health care professionals

Health economic model (opens in new window)

Health economic model including report and webtool for countryor region specific estimates

Final event (opens in new window)

Final event to present the results and outcomes in the European Parliament

Generic model for economic assessment on a hospital level (opens in new window)

Generic model for economic assessment on a hospital level by analysing the qualitative and economic effects due to ENVISION implementation, including a written report.

COVID-19 use cases and ICU scenarios (opens in new window)

Report describing a minimum of 10 different use cases and 10 different scenarios of COVID-19 patient surveillance in ICUs

ENVISION website (opens in new window)

ENVISION website with dedicated areas for different stakeholder groups

Publications

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort (opens in new window)

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 (opens in new window)

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 (opens in new window)

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

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