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

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.