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

Projektinformationen

ENVISION

ID Finanzhilfevereinbarung: 101015930

DOI

10.3030/101015930

Projekt abgeschlossen

EK-Unterschriftsdatum 13 Oktober 2020

Startdatum 1 Dezember 2020

Enddatum 31 Juli 2023

Finanziert unter

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

Gesamtkosten

€ 5 660 486,25

EU-Beitrag

€ 4 874 111,25

Koordiniert durch

JOHANN WOLFGANG GOETHE-UNIVERSITAET FRANKFURT AM MAIN
Germany

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Documents, reports (11)

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

Final implementation report
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

Generic model for economic assessment on a hospital level

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

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

Websites, patent fillings, videos etc. (1)

ENVISION website

ENVISION website with dedicated areas for different stakeholder groups

Veröffentlichungen

Peer reviewed articles (3)

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort

Autoren: 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
Veröffentlicht in: Critical Care, Ausgabe 295 (2021), 2021, Seite(n) 25, ISSN 1364-8535
Herausgeber: BMC
DOI: 10.1186/s13054-021-03720-4

ENVISION – Improve intensive care of COVID-19 patients with artificial intelligence

Autoren: Alpo Olavi Värri, Antti Kallonen, Hannu Nieminen, Mark Van Gils
Veröffentlicht in: Finnish Journal of EHealth and EWelfare, Ausgabe 13 (4), 2021, Seite(n) 449-453, ISSN 1798-0798
Herausgeber: 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

Autoren: 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
Veröffentlicht in: Springer Nature, 2021, ISSN 1364-8535
Herausgeber: BMC
DOI: 10.6084/m9.figshare.15184814