An adaptive network model for AI-assisted monitoring and management of neonatal respiratory distress
Nisrine Mokadem (Vrije Universiteit Amsterdam)
Fakhra Jabeen (TU Delft - Safety and Security Science)
Jan Treur (Vrije Universiteit Amsterdam)
H. Rob Taal (Erasmus MC)
Peter H.M.P. Roelofsma (Erasmus MC)
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Abstract
This article presents the use of second-order adaptive network models of hospital teams consisting of doctors and nurses, interacting together. A variety of scenarios are modelled and simulated, in relation with respiratory distress of a neonate, along with the integration of an AI-Coach for monitoring and support of such teams and of organizational learning. The research highlights the benefits of introducing a virtual AI-Coach in a hospital setting. The practical application setting revolves around a medical team responsible for managing neonates with respiratory distress. In this setting an AI-Coach act as an additional team member, to ensure correct execution of medical procedure. Through simulation experiments, the adaptive network models demonstrate that the AI-Coach not only aids in maintaining correct medical procedure execution but also facilitates organizational learning, leading to significant improvements in procedure adherence and error reduction during neonatal care.
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