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 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 ethicaltechnical and legal implications of using machine learning in this context.

Motivation

This is a self-assessment conducted jointly by a team of independent experts together with the prime stakeholder of this use case. The main motivation of this work is to verify if the rate of lives saved could be increased by using AI, and at the same time to identify possible risks and pitfalls of using the AI system assessed here, and to provide recommendations to key stakeholders.

Jointly with the Emergency Medical Services Copenhagen, we completed the first part of our trustworthy AI assessment.

Stig Nikolaj Fasmer Blomberg,

Senior Advisor, Emergency Medical Services Copenhagen

Resources

What did we learn in assessing Trustworthy AI in practice?
Roberto V. Zicari, Z-Inspection® Initiative
AI Ethics online–Chalmers, April 20, 2021

YouTube: https://www.youtube.com/watch?v=Jt63ZUbrBJM

Download Presentation:
Zicari.CHALMERSApril20.2021

……………………………………………………………………………………………………………………………………………………..

On Assessing Trustworthy AI in Healthcare 
Best Practice for Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls

Front. Hum. Dyn. | doi: 10.3389/fhumd.2021.673104

https://www.frontiersin.org/articles/10.3389/fhumd.2021.673104/abstract

ORIGINAL RESEARCH.  The full article will be available online soon.

……………………………………………………………

For the Press: More information here.