FlowFusion Case Study: Governability Analysis of an AI-Assisted Clinical Triage System
Abstract
Healthcare systems increasingly deploy artificial intelligence tools to assist with clinical triage, diagnosis prioritization, and patient flow management. These systems operate in environments characterized by high decision pressure, limited time for review, and potentially severe consequences. This case study applies the FlowFusion institutional governance architecture to evaluate whether an AI-assisted clinical triage system remains governable, observable, reversible, and correctable under real-world healthcare conditions. The analysis examines the decision architecture, structural fragility, and governance risks associated with automated triage prioritization.
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Ethics and Social Impacts of AI
Safety Systems Engineering in Autonomy
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 March 2026
- Language
- EN
- Document type
- Preprint