On the Ethics of AI-based Algorithmic decision-making in Healthcare.

Assessing Trustworthy AI. Best Practice: Machine learning as a supportive tool to recognize cardiac arrest in emergency calls.

In cooperation with

Emergency Medical Services Copenhagen, and
Department of Clinical Medicine, University of Copenhagen, Denmark

Approach

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 result of this analysis is published here.

We started to work with Stig Nikolaj Blomberg and his team and apply Z-inspection® to assess the ethicaltechnical and legal implications of using machine learning in this context.

Stig Nikolaj Fasmer Blomberg,

Senior Advisor, Emergency Medical Services Copenhagen