This research work highlights the need for AI-powered applications and their usages for the
optimization of information flow processes in the medical sector, from the perspective of how
AI-agents can impact human-machine interaction (HCI) for acquiring relevant and necessary
information in emergency department (ED). This study investigates how AI-agents can be applied to manage situations of patient related unexpected experiences, such as long waiting times,
overcrowding issues, and high number of patients leaving without being diagnosed. For knowledge acquisition, we incorporated modelling workshop techniques for gathering domain information from the domain experts in the context of emergency department in Karolinska Hospi-tal, Solna, Stockholm, Sweden, and for designing the AI-agent utilizing NLP techniques. We dis-cuss how the proposed solution can be used as an assistant to healthcare practitioners and workers to improve medical assistance in various medical procedures to increase flow and to reduce workloads and anxiety levels. The implementation part of this work is based on the natural language processing (NLP) techniques that help to develop the intelligent behavior for information acquisition and its
retriev-al in a natural way to support patients/relatives’ communication with the healthcare organization efficiently and in a natural way.
Fareedi, Abid Ali; Ghazawneh, Ahmad; and Bergquist, Magnus, "Artificial Intelligence Agents and Knowledge Acquisition in Health Information System" (2022). MCIS 2022 Proceedings. 8.