Clinical Automata in Fuzzy Arden Syntax
Julia Liepold, Moritz Grob, Владик Крейнович, Robert A. Jenders, Klaus-Peter Adlassnig · Studies in health technology and informatics · 2025
Fuzzy automata provide a powerful framework for clinical diagnostics and patient monitoring by integrating uncertainty handling, making them ideal for medical decision-making with often imprecise data. Unlike classical automata, fuzzy automata support degrees of membership, allowing more nuanced interpretations of symptoms and disease progression. They can be seamlessly abstracted from Arden Syntax, a widely-adopted clinical rule-based language, by mapping medical logic onto fuzzy state transitions. These visualizations enhance clinical monitoring, making them an invaluable tool for modern healthcare systems by providing a flexible, adaptive approach to managing complex health case scenarios.