Virtual coaches can support patients who need continuous rehabilitation due to an acute illness in the home environment. These coaching systems have to give medically correct instructions on the one hand and on the other hand respond individually to the patient. Hereby, machine learning algorithms could enable the adaptation and personalization of the rehabilitation process. In order to capture the necessary medical knowledge in a structured form and let the system technically make use of it, approaches of conceptual modelling have proved to be effective. On the basis of a virtual coaching scenario, we demonstrate how such a coaching application could be conceptually structured with the help of the goal-oriented modeling language i∗ in comparison to BPMN as process modelling approach and how machine learning algorithms could be implemented.
|Titel||Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022|
|Redakteure/-innen||Brigitte Seroussi, Patrick Weber, Ferdinand Dhombres, Cyril Grouin, Jan-David Liebe, Jan-David Liebe, Jan-David Liebe, Sylvia Pelayo, Andrea Pinna, Bastien Rance, Bastien Rance, Lucia Sacchi, Adrien Ugon, Adrien Ugon, Arriel Benis, Parisis Gallos|
|Publikationsstatus||Veröffentlicht - 25 Mai 2022|