Publication
Utilizing Expert Knowledge to Support Medical Emergency Call Handling
Carsten Maletzki; Eric Rietzke; Ralph Bergmann
In: Christoph Beierle; Marco Ragni; Frieder Stolzenburg; Kai Sauerwald; Matthias Thimm (Hrsg.). Proceedings of the 8th Workshop on Formal and Cognitive Reasoning co-located with the 45th German Conference on Artificial Intelligence (KI 2022), Virtual Event, Trier, Germany, September 19, 2022. Workshop on Formal and Cognitive Reasoning (FCR-2022), 8th Workshop on Formal and Cognitive Reasoning, located at 45th German Conference on Artificial Intelligence (KI 2022), September 19-23, Trier, Germany, Pages 79-89, CEUR Workshop Proceedings (CEUR-WS), Vol. 3242, CEUR-WS.org, 10/2022.
Abstract
Medical emergency calls require fast decisions from call takers about triage and appropriate responses. Call takers approach this challenge by deriving decisions from mental pictures they create by assessing available information with their expert knowledge. Established questionnaire-based support systems in this context experience hesitant acceptance while an alternative that is currently researched suffers from its complex approach to utilizing formalized expert knowledge. This paper addresses the latter by designing an Ontology- and Data-Driven Expert System (ODD-ES) for call takers of medical emergency calls. ODD-ES aims at supporting call takers with recommendations regarding decisions and questions that result from inferred artificial mental pictures. The knowledge base used to infer artificial mental pictures builds on semantically modeled functions to achieve maintainability and an integration of symbolic and subsymbolic Artificial Intelligence (AI). To make recommendations and handle responses of call takers, ODD-ES proposes a component called Copilot that will be in the focus of our future work.