Assessing Trustworthy AI. Best Practice: Machine learning as a supportive tool to recognize cardiac arrest in emergency calls.
We started assessing this new use case in cooperation with Emergency Medical Services Copenhagen, and the Department of Clinical Medicine, University of Copenhagen, Denmark
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.
You can read more here