Emergency medical dispatchers fail to identify approximately 25% of cases of out of hospital cardiac arrest, thus loose the opportunity to provide the caller instructions in cardiopulmonary resuscitation.
A team lead by Stig Nikolaj Blomberg (Emergency Medical Services Copenhagen, and Department of Clinical Medicine, University of Copenhagen, Denmark) examined whether a machine learning framework could recognize out-of-hospital cardiac arrest from audio files of calls to the emergency medical dispatch center.
The results of a retrospective study are published here.
The results of a randomized clinical trial are published here.
We are working with Stig Nikolaj Blomberg and his team and apply Z-inspection® to assess the ethical, technical and legal implications of using machine learning in this context.