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Machine learning in intensive care medicine: ready for take-off?

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Fleuren, Lucas M 
Thoral, Patrick 
Shillan, Duncan 
Elbers, Paul WG 

Abstract

In 1986 the world was shaken by the Challenger space shuttle disaster. In the years that followed, the American National Aeronautics and Space Administration (NASA) called for a strategy change in space technology development [1]. Allowing technology to be developed without a specific space program in mind was central to the new strategy [2]. In order to evaluate resulting projects with no direct contribution to a space mission, NASA introduced the general concept of technology readiness levels (TRLs) [3]. These nine levels, adopted by many EU institutions, assess the maturity level of technology and estimate its readiness to fly.

Description

Keywords

Critical Care, Humans, Intensive Care Units, Machine Learning, Medicine

Journal Title

Intensive Care Med

Conference Name

Journal ISSN

0342-4642
1432-1238

Volume Title

46

Publisher

Springer Science and Business Media LLC

Rights

All rights reserved