Co-design of a trustworthy AI-based prognostic tool for predicting patient outcome in acute stroke

This paper reports a descriptive, process-oriented case study of the application of Z-Inspection®, an ethically aligned co-design methodology, in the early design phase of an artificial intelligence (AI) system for healthcare. The methodology was applied within the Horizon Europe project VALIDATE [1], which develops and validates a prognostic clinical decision support system (CDSS) to support treatment decisions in acute ischaemic stroke. An interdisciplinary team of Z-Inspection® experts, AI developers, and clinical stakeholders jointly identified ethical, legal, and technical issues relevant to the planned system. The assessment resulted in 22 ethical issues, 12 dilemmas, 18 risks, and 48 derived requirements, each mapped to the European Commission’s trustworthy AI principles. The identified issues, dilemmas, risks, and derived requirements constitute the primary findings of this descriptive case study and document how general trustworthy-AI principles were translated into context-specific technical, clinical, governance, and organisational requirements. By documenting the process and publishing the complete requirements, the study provides a detailed case for critical scrutiny and potential uptake in other healthcare AI projects, though its transferability and scalability remain to be established in further studies.