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

Project Information

ENVISION

Grant agreement ID: 101015930

DOI 10.3030/101015930

Project closed

EC signature date 13 October 2020

Start date 1 December 2020

End date 31 July 2023

Funded under

• SOCIETAL CHALLENGES - Health, demographic change and well-being

Total cost € 5 660 486,25

EU contribution € 4 874 111,25

Coordinated by

JOHANN WOLFGANG GOETHE-UNIVERSITAET FRANKFURT AM MAIN
Germany

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

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