Assessing Trustworthy AI. Best Practices

We apply Z-Inspection® to real use cases.

Assessing Trustworthy AI. Best Practice: AI for Predicting Cardiovascular Risks

We have used and tested Z-Inspection® by evaluating a non invasive AI medical device which was designed to assist medical doctors in the diagnosis of cardiovascular diseases.

  Assessment Completed.

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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

Assessment in progress.

Assessing Trustworthy AI. Best Practices

“Ethical impact evaluation involves evaluating the ethical impact of a technology’s use, not just on its users, but often, also on those indirectly affected, such as their friends and families, communities, society as a whole, and the planet.“

–Peters et al.

Assessing Trustworthy AI. Best Practice: Deep Learning based Skin Lesion Classifiers.

In cooperation with

German Research Center for Artificial Intelligence GmbH (DFKI)

 Assessment in progress.

Assessing Trustworthy AI. Best Practice: Deep Learning for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients.

In cooperation with

Department of Information Engineering and Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health – University of Brescia, Brescia, Italy